publications
Please also see Google Scholar for an updated list.
2026
PolySAE: Modeling Feature Interactions in Sparse Autoencoders via Polynomial Decoding
International Conference on Machine Learning (ICML)
BibTeX
@inproceedings{2026_PolySAE_ICML,
author = {P. Koromilas and A. D. Demou and J. Oldfield and Y. Panagakis and M. A. Nicolaou},
title = {PolySAE: Modeling Feature Interactions in Sparse Autoencoders via Polynomial Decoding},
booktitle = {International Conference on Machine Learning (ICML)},
year = {2026}
}APAKoromilas, P., Demou, A. D., Oldfield, J., Panagakis, Y., & Nicolaou, M. A. (2026). PolySAE: Modeling Feature Interactions in Sparse Autoencoders via Polynomial Decoding. International Conference on Machine Learning (ICML).
MLAKoromilas, P., et al. "PolySAE: Modeling Feature Interactions in Sparse Autoencoders via Polynomial Decoding." International Conference on Machine Learning (ICML), 2026.
IEEEP. Koromilas, A. D. Demou, J. Oldfield, Y. Panagakis, and M. A. Nicolaou, "PolySAE: Modeling Feature Interactions in Sparse Autoencoders via Polynomial Decoding," in International Conference on Machine Learning (ICML), 2026.
Neural Collapse by Design: Learning Class Prototypes on the Hypersphere
International Conference on Machine Learning (ICML)
BibTeX
@inproceedings{2026_NeuralCollapse_ICML,
author = {P. Koromilas and T. Giannakopoulos and M. A. Nicolaou and Y. Panagakis},
title = {Neural Collapse by Design: Learning Class Prototypes on the Hypersphere},
booktitle = {International Conference on Machine Learning (ICML)},
year = {2026}
}APAKoromilas, P., Giannakopoulos, T., Nicolaou, M. A., & Panagakis, Y. (2026). Neural Collapse by Design: Learning Class Prototypes on the Hypersphere. International Conference on Machine Learning (ICML).
MLAKoromilas, P., et al. "Neural Collapse by Design: Learning Class Prototypes on the Hypersphere." International Conference on Machine Learning (ICML), 2026.
IEEEP. Koromilas, T. Giannakopoulos, M. A. Nicolaou, and Y. Panagakis, "Neural Collapse by Design: Learning Class Prototypes on the Hypersphere," in International Conference on Machine Learning (ICML), 2026.
Interpretable Music Harmonic Analysis Through Multilinear Mixture of Experts
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
BibTeX
@inproceedings{2026_Triantafyllou_ICASSP,
author = {T. Triantafyllou and M. A. Nicolaou and Y. Panagakis},
title = {Interpretable Music Harmonic Analysis Through Multilinear Mixture of Experts},
booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
year = {2026}
}APATriantafyllou, T., Nicolaou, M. A., & Panagakis, Y. (2026). Interpretable Music Harmonic Analysis Through Multilinear Mixture of Experts. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
MLATriantafyllou, T., et al. "Interpretable Music Harmonic Analysis Through Multilinear Mixture of Experts." IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2026.
IEEET. Triantafyllou, M. A. Nicolaou, and Y. Panagakis, "Interpretable Music Harmonic Analysis Through Multilinear Mixture of Experts," in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2026.
Disentangling Local and Global Semantics in Diffusion Models for Image Editing
International Journal of Computer Vision (IJCV)
BibTeX
@article{2026_Plitsis_IJCV,
author = {M. Plitsis and T. Kouzelis and P. Koromilas and V. Katsouros and M. A. Nicolaou and Y. Panagakis},
title = {Disentangling Local and Global Semantics in Diffusion Models for Image Editing},
journal = {International Journal of Computer Vision (IJCV)},
year = {2026}
}APAPlitsis, M., Kouzelis, T., Koromilas, P., Katsouros, V., Nicolaou, M. A., & Panagakis, Y. (2026). Disentangling Local and Global Semantics in Diffusion Models for Image Editing. International Journal of Computer Vision (IJCV).
MLAPlitsis, M., et al. "Disentangling Local and Global Semantics in Diffusion Models for Image Editing." International Journal of Computer Vision (IJCV), 2026.
IEEEM. Plitsis, T. Kouzelis, P. Koromilas, V. Katsouros, M. A. Nicolaou, and Y. Panagakis, "Disentangling Local and Global Semantics in Diffusion Models for Image Editing," International Journal of Computer Vision (IJCV), 2026.
Artificial Intelligence-Based Heliostat Characterisation Through Synthetic Data
Engineering Applications of Artificial Intelligence
BibTeX
@article{2026_GarciaMoreno_EAAI,
author = {J. Moreno García-Moreno and K. Milidonis and G. Kourmouli and M. A. Nicolaou},
title = {Artificial Intelligence-Based Heliostat Characterisation Through Synthetic Data},
journal = {Engineering Applications of Artificial Intelligence (EAAI)},
year = {2026}
}APAMoreno García-Moreno, J., Milidonis, K., Kourmouli, G., & Nicolaou, M. A. (2026). Artificial Intelligence-Based Heliostat Characterisation Through Synthetic Data. Engineering Applications of Artificial Intelligence (EAAI).
MLAMoreno García-Moreno, J., et al. "Artificial Intelligence-Based Heliostat Characterisation Through Synthetic Data." Engineering Applications of Artificial Intelligence (EAAI), 2026.
IEEEJ. Moreno García-Moreno, K. Milidonis, G. Kourmouli, and M. A. Nicolaou, "Artificial Intelligence-Based Heliostat Characterisation Through Synthetic Data," Engineering Applications of Artificial Intelligence (EAAI), 2026.
2025
Towards Interpretability Without Sacrifice: Faithful Dense Layer Decomposition with Mixture of Decoders
Advances in Neural Information Processing Systems (NeurIPS)
BibTeX
@inproceedings{2025_MoD_NeurIPS,
author = {J. Oldfield and S. Im and Y. Li and M. A. Nicolaou and I. Patras and G. G. Chrysos},
title = {Towards Interpretability Without Sacrifice: Faithful Dense Layer Decomposition with Mixture of Decoders},
booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
year = {2025}
}APAOldfield, J., Im, S., Li, Y., Nicolaou, M. A., Patras, I., & Chrysos, G. G. (2025). Towards Interpretability Without Sacrifice: Faithful Dense Layer Decomposition with Mixture of Decoders. Advances in Neural Information Processing Systems (NeurIPS).
MLAOldfield, J., et al. "Towards Interpretability Without Sacrifice: Faithful Dense Layer Decomposition with Mixture of Decoders." Advances in Neural Information Processing Systems (NeurIPS), 2025.
IEEEJ. Oldfield, S. Im, Y. Li, M. A. Nicolaou, I. Patras, and G. G. Chrysos, "Towards Interpretability Without Sacrifice: Faithful Dense Layer Decomposition with Mixture of Decoders," in Advances in Neural Information Processing Systems (NeurIPS), 2025.
Rethinking Objectives for Multi-View and Multi-Modal Contrastive Learning
UniReps Workshop, Advances in Neural Information Processing Systems (NeurIPS)
BibTeX
@inproceedings{2025_Koromilas_NeurIPSW,
author = {P. Koromilas and E. Georgiou and G. Bouritsas and T. Giannakopoulos and M. A. Nicolaou and Y. Panagakis},
title = {Rethinking Objectives for Multi-View and Multi-Modal Contrastive Learning},
booktitle = {UniReps Workshop, Advances in Neural Information Processing Systems (NeurIPS)},
year = {2025}
}APAKoromilas, P., Georgiou, E., Bouritsas, G., Giannakopoulos, T., Nicolaou, M. A., & Panagakis, Y. (2025). Rethinking Objectives for Multi-View and Multi-Modal Contrastive Learning. UniReps Workshop, Advances in Neural Information Processing Systems (NeurIPS).
MLAKoromilas, P., et al. "Rethinking Objectives for Multi-View and Multi-Modal Contrastive Learning." UniReps Workshop, Advances in Neural Information Processing Systems (NeurIPS), 2025.
IEEEP. Koromilas, E. Georgiou, G. Bouritsas, T. Giannakopoulos, M. A. Nicolaou, and Y. Panagakis, "Rethinking Objectives for Multi-View and Multi-Modal Contrastive Learning," in UniReps Workshop, Advances in Neural Information Processing Systems (NeurIPS), 2025.
Global high-resolution ultrafine particle number concentrations through data fusion with machine learning
Scientific Data
BibTeX
@article{2025_Georgiades_SciData,
author = {P. Georgiades and M. Kohl and M. A. Nicolaou and T. Christoudias and A. Pozzer and C. Dovrolis and J. Lelieveld},
title = {Global high-resolution ultrafine particle number concentrations through data fusion with machine learning},
journal = {Scientific Data},
year = {2025}
}APAGeorgiades, P., Kohl, M., Nicolaou, M. A., Christoudias, T., Pozzer, A., Dovrolis, C., & Lelieveld, J. (2025). Global high-resolution ultrafine particle number concentrations through data fusion with machine learning. Scientific Data.
MLAGeorgiades, P., et al. "Global high-resolution ultrafine particle number concentrations through data fusion with machine learning." Scientific Data, 2025.
IEEEP. Georgiades, M. Kohl, M. A. Nicolaou, T. Christoudias, A. Pozzer, C. Dovrolis, and J. Lelieveld, "Global high-resolution ultrafine particle number concentrations through data fusion with machine learning," Scientific Data, 2025.
Artificial intelligence-aided generative design of non-imaging secondary reflector for linear Fresnel concentrating collector
Solar Energy
BibTeX
@article{2025_GarciaMoreno_SolarEnergy,
author = {J. M. García-Moreno and A. C. Montenon and M. A. Nicolaou and W. Lipiński and K. Milidonis},
title = {Artificial intelligence-aided generative design of non-imaging secondary reflector for linear Fresnel concentrating collector},
journal = {Solar Energy},
year = {2025}
}APAGarcía-Moreno, J. M., Montenon, A. C., Nicolaou, M. A., Lipiński, W., & Milidonis, K. (2025). Artificial intelligence-aided generative design of non-imaging secondary reflector for linear Fresnel concentrating collector. Solar Energy.
MLAGarcía-Moreno, J. M., et al. "Artificial intelligence-aided generative design of non-imaging secondary reflector for linear Fresnel concentrating collector." Solar Energy, 2025.
IEEEJ. M. García-Moreno, A. C. Montenon, M. A. Nicolaou, W. Lipiński, and K. Milidonis, "Artificial intelligence-aided generative design of non-imaging secondary reflector for linear Fresnel concentrating collector," Solar Energy, 2025.
Immersed boundary–lattice Boltzmann mesoscale method for wetting problems
Physical Review E
BibTeX
@article{2025_Bellantoni_PRE,
author = {E. Bellantoni and F. Guglietta and F. Pelusi and M. Desbrun and K. Um and M. A. Nicolaou and N. Savva and M. Sbragaglia},
title = {Immersed boundary–lattice Boltzmann mesoscale method for wetting problems},
journal = {Physical Review E},
year = {2025}
}APABellantoni, E., Guglietta, F., Pelusi, F., Desbrun, M., Um, K., Nicolaou, M. A., Savva, N., & Sbragaglia, M. (2025). Immersed boundary–lattice Boltzmann mesoscale method for wetting problems. Physical Review E.
MLABellantoni, E., et al. "Immersed boundary–lattice Boltzmann mesoscale method for wetting problems." Physical Review E, 2025.
IEEEE. Bellantoni, F. Guglietta, F. Pelusi, M. Desbrun, K. Um, M. A. Nicolaou, N. Savva, and M. Sbragaglia, "Immersed boundary–lattice Boltzmann mesoscale method for wetting problems," Physical Review E, 2025.
2024
Multilinear Mixture of Experts: Scalable Expert Specialization through Factorization
Advances in Neural Information Processing Systems (NeurIPS)
BibTeX
@inproceedings{2024_muMoE_NeurIPS,
author = {J. Oldfield and M. Georgopoulos and G. G. Chrysos and C. Tzelepis and Y. Panagakis and M. A. Nicolaou and J. Deng and I. Patras},
title = {Multilinear Mixture of Experts: Scalable Expert Specialization through Factorization},
booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
year = {2024}
}APAOldfield, J., Georgopoulos, M., Chrysos, G. G., Tzelepis, C., Panagakis, Y., Nicolaou, M. A., Deng, J., & Patras, I. (2024). Multilinear Mixture of Experts: Scalable Expert Specialization through Factorization. Advances in Neural Information Processing Systems (NeurIPS).
MLAOldfield, J., et al. "Multilinear Mixture of Experts: Scalable Expert Specialization through Factorization." Advances in Neural Information Processing Systems (NeurIPS), 2024.
IEEEJ. Oldfield, M. Georgopoulos, G. G. Chrysos, C. Tzelepis, Y. Panagakis, M. A. Nicolaou, J. Deng, and I. Patras, "Multilinear Mixture of Experts: Scalable Expert Specialization through Factorization," in Advances in Neural Information Processing Systems (NeurIPS), 2024.
Enabling Local Editing in Diffusion Models by Joint and Individual Component Analysis
British Machine Vision Conference (BMVC)
BibTeX
@inproceedings{2024_Kouzelis_BMVC,
author = {T. Kouzelis and M. Plitsis and M. A. Nicolaou and Y. Panagakis},
title = {Enabling Local Editing in Diffusion Models by Joint and Individual Component Analysis},
booktitle = {British Machine Vision Conference (BMVC)},
year = {2024}
}APAKouzelis, T., Plitsis, M., Nicolaou, M. A., & Panagakis, Y. (2024). Enabling Local Editing in Diffusion Models by Joint and Individual Component Analysis. British Machine Vision Conference (BMVC).
MLAKouzelis, T., et al. "Enabling Local Editing in Diffusion Models by Joint and Individual Component Analysis." British Machine Vision Conference (BMVC), 2024.
IEEET. Kouzelis, M. Plitsis, M. A. Nicolaou, and Y. Panagakis, "Enabling Local Editing in Diffusion Models by Joint and Individual Component Analysis," in British Machine Vision Conference (BMVC), 2024.
Bridging the gap between mini-batch and asymptotic analysis in contrastive learning: From InfoNCE to Kernel-based losses
International Conference on Machine Learning (ICML)
BibTeX
@inproceedings{2024_Koromilas_ICML,
author = {P. Koromilas and G. Bouritsas and M. A. Nicolaou and Y. Panagakis},
title = {Bridging the gap between mini-batch and asymptotic analysis in contrastive learning: From InfoNCE to Kernel-based losses},
booktitle = {International Conference on Machine Learning (ICML)},
year = {2024}
}APAKoromilas, P., Bouritsas, G., Nicolaou, M. A., & Panagakis, Y. (2024). Bridging the gap between mini-batch and asymptotic analysis in contrastive learning: From InfoNCE to Kernel-based losses. International Conference on Machine Learning (ICML).
MLAKoromilas, P., et al. "Bridging the gap between mini-batch and asymptotic analysis in contrastive learning: From InfoNCE to Kernel-based losses." International Conference on Machine Learning (ICML), 2024.
IEEEP. Koromilas, G. Bouritsas, M. A. Nicolaou, and Y. Panagakis, "Bridging the gap between mini-batch and asymptotic analysis in contrastive learning: From InfoNCE to Kernel-based losses," in International Conference on Machine Learning (ICML), 2024.
Bilinear Models of Parts and Appearances in Generative Adversarial Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
BibTeX
@article{2024_Oldfield_TPAMI,
author = {J. Oldfield and C. Tzelepis and M. A. Nicolaou and Y. Panagakis and I. Patras},
title = {Bilinear Models of Parts and Appearances in Generative Adversarial Networks},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
year = {2024}
}APAOldfield, J., Tzelepis, C., Nicolaou, M. A., Panagakis, Y., & Patras, I. (2024). Bilinear Models of Parts and Appearances in Generative Adversarial Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
MLAOldfield, J., et al. "Bilinear Models of Parts and Appearances in Generative Adversarial Networks." IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
IEEEJ. Oldfield, C. Tzelepis, M. A. Nicolaou, Y. Panagakis, and I. Patras, "Bilinear Models of Parts and Appearances in Generative Adversarial Networks," IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
Tensor Methods in Deep Learning
Signal Processing and Machine Learning Theory, Elsevier (book chapter)
BibTeX
@incollection{2024_TMDL_Elsevier,
author = {Y. Panagakis and J. Kossaifi and G. Chrysos and J. Oldfield and M. A. Nicolaou and S. Zafeiriou and A. Anandkumar},
title = {Tensor Methods in Deep Learning},
booktitle = {Signal Processing and Machine Learning Theory, Elsevier (book chapter)},
year = {2024}
}APAPanagakis, Y., Kossaifi, J., Chrysos, G., Oldfield, J., Nicolaou, M. A., Zafeiriou, S., & Anandkumar, A. (2024). Tensor Methods in Deep Learning. Signal Processing and Machine Learning Theory, Elsevier (book chapter).
MLAPanagakis, Y., et al. "Tensor Methods in Deep Learning." Signal Processing and Machine Learning Theory, Elsevier (book chapter), 2024.
IEEEY. Panagakis, J. Kossaifi, G. Chrysos, J. Oldfield, M. A. Nicolaou, S. Zafeiriou, and A. Anandkumar, "Tensor Methods in Deep Learning," Signal Processing and Machine Learning Theory, Elsevier (book chapter), 2024.
2023
Parts of Speech-Grounded Subspaces in Vision-Language Models
Advances in Neural Information Processing Systems (NeurIPS)
BibTeX
@inproceedings{2023_Oldfield_NeurIPS,
author = {J. Oldfield and C. Tzelepis and M. A. Nicolaou and Y. Panagakis and I. Patras},
title = {Parts of Speech-Grounded Subspaces in Vision-Language Models},
booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
year = {2023}
}APAOldfield, J., Tzelepis, C., Nicolaou, M. A., Panagakis, Y., & Patras, I. (2023). Parts of Speech-Grounded Subspaces in Vision-Language Models. Advances in Neural Information Processing Systems (NeurIPS).
MLAOldfield, J., et al. "Parts of Speech-Grounded Subspaces in Vision-Language Models." Advances in Neural Information Processing Systems (NeurIPS), 2023.
IEEEJ. Oldfield, C. Tzelepis, M. A. Nicolaou, Y. Panagakis, and I. Patras, "Parts of Speech-Grounded Subspaces in Vision-Language Models," in Advances in Neural Information Processing Systems (NeurIPS), 2023.
PandA: Unsupervised Learning of Parts and Appearances in the Feature Maps of GANs
International Conference on Learning Representations (ICLR)
BibTeX
@inproceedings{2023_PandA_ICLR,
author = {J. Oldfield and C. Tzelepis and M. A. Nicolaou and Y. Panagakis and I. Patras},
title = {PandA: Unsupervised Learning of Parts and Appearances in the Feature Maps of GANs},
booktitle = {International Conference on Learning Representations (ICLR)},
year = {2023}
}APAOldfield, J., Tzelepis, C., Nicolaou, M. A., Panagakis, Y., & Patras, I. (2023). PandA: Unsupervised Learning of Parts and Appearances in the Feature Maps of GANs. International Conference on Learning Representations (ICLR).
MLAOldfield, J., et al. "PandA: Unsupervised Learning of Parts and Appearances in the Feature Maps of GANs." International Conference on Learning Representations (ICLR), 2023.
IEEEJ. Oldfield, C. Tzelepis, M. A. Nicolaou, Y. Panagakis, and I. Patras, "PandA: Unsupervised Learning of Parts and Appearances in the Feature Maps of GANs," in International Conference on Learning Representations (ICLR), 2023.
Multimodal Prediction of Alexithymia from Physiological and Audio Signals
International Conference on Affective Computing and Intelligent Interaction (ACII)
BibTeX
@inproceedings{2023_Filippou_ACII,
author = {V. Filippou and N. Theodosiou and M. A. Nicolaou and G. Panagiotou},
title = {Multimodal Prediction of Alexithymia from Physiological and Audio Signals},
booktitle = {International Conference on Affective Computing and Intelligent Interaction (ACII)},
year = {2023}
}APAFilippou, V., Theodosiou, N., Nicolaou, M. A., Panagiotou, G., et al. (2023). Multimodal Prediction of Alexithymia from Physiological and Audio Signals. International Conference on Affective Computing and Intelligent Interaction (ACII).
MLAFilippou, V., et al. "Multimodal Prediction of Alexithymia from Physiological and Audio Signals." International Conference on Affective Computing and Intelligent Interaction (ACII), 2023.
IEEEV. Filippou, N. Theodosiou, M. A. Nicolaou, G. Panagiotou, et al., "Multimodal Prediction of Alexithymia from Physiological and Audio Signals," in International Conference on Affective Computing and Intelligent Interaction (ACII), 2023.
Locality-preserving Directions: Interpreting the Latent Space of Satellite Image GANs
IEEE Geoscience and Remote Sensing Letters (GRSL)
BibTeX
@article{2023_Kourmouli_GRSL,
author = {G. Kourmouli and N. Kostagiolas and M. A. Nicolaou and Y. Panagakis},
title = {Locality-preserving Directions: Interpreting the Latent Space of Satellite Image GANs},
journal = {IEEE Geoscience and Remote Sensing Letters (GRSL)},
year = {2023}
}APAKourmouli, G., Kostagiolas, N., Nicolaou, M. A., & Panagakis, Y. (2023). Locality-preserving Directions: Interpreting the Latent Space of Satellite Image GANs. IEEE Geoscience and Remote Sensing Letters (GRSL).
MLAKourmouli, G., et al. "Locality-preserving Directions: Interpreting the Latent Space of Satellite Image GANs." IEEE Geoscience and Remote Sensing Letters (GRSL), 2023.
IEEEG. Kourmouli, N. Kostagiolas, M. A. Nicolaou, and Y. Panagakis, "Locality-preserving Directions: Interpreting the Latent Space of Satellite Image GANs," IEEE Geoscience and Remote Sensing Letters (GRSL), 2023.
Towards Explainable and Transferable Deep Downscaling of Atmospheric Pollutants
IEEE Geoscience and Remote Sensing Letters (GRSL)
BibTeX
@article{2023_Ashiotis_GRSL,
author = {G. Ashiotis and P. Georgiades and T. Christoudias and M. A. Nicolaou},
title = {Towards Explainable and Transferable Deep Downscaling of Atmospheric Pollutants},
journal = {IEEE Geoscience and Remote Sensing Letters (GRSL)},
year = {2023}
}APAAshiotis, G., Georgiades, P., Christoudias, T., & Nicolaou, M. A. (2023). Towards Explainable and Transferable Deep Downscaling of Atmospheric Pollutants. IEEE Geoscience and Remote Sensing Letters (GRSL).
MLAAshiotis, G., et al. "Towards Explainable and Transferable Deep Downscaling of Atmospheric Pollutants." IEEE Geoscience and Remote Sensing Letters (GRSL), 2023.
IEEEG. Ashiotis, P. Georgiades, T. Christoudias, and M. A. Nicolaou, "Towards Explainable and Transferable Deep Downscaling of Atmospheric Pollutants," IEEE Geoscience and Remote Sensing Letters (GRSL), 2023.
2022
MMATR: Lightweight Tensor-based Regression for Multimodal Sentiment Analysis
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
BibTeX
@inproceedings{2022_MMATR_ICASSP,
author = {P. Koromilas and T. Giannakopoulos and M. A. Nicolaou and Y. Panagakis},
title = {MMATR: Lightweight Tensor-based Regression for Multimodal Sentiment Analysis},
booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
year = {2022}
}APAKoromilas, P., Giannakopoulos, T., Nicolaou, M. A., & Panagakis, Y. (2022). MMATR: Lightweight Tensor-based Regression for Multimodal Sentiment Analysis. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
MLAKoromilas, P., et al. "MMATR: Lightweight Tensor-based Regression for Multimodal Sentiment Analysis." IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022.
IEEEP. Koromilas, T. Giannakopoulos, M. A. Nicolaou, and Y. Panagakis, "MMATR: Lightweight Tensor-based Regression for Multimodal Sentiment Analysis," in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022.
AI for Air Quality: Leveraging Data Fusion for Deep Downscaling of Atmospheric Pollutants
Machine Learning for Earth Observation Workshop (MACLEAN), ECML/PKDD — Best Paper Award
BibTeX
@inproceedings{2022_Ashiotis_MACLEAN,
author = {G. Ashiotis and E. Tsigkanos and T. Christoudias and M. A. Nicolaou},
title = {AI for Air Quality: Leveraging Data Fusion for Deep Downscaling of Atmospheric Pollutants},
booktitle = {Machine Learning for Earth Observation Workshop (MACLEAN), ECML/PKDD},
year = {2022}
}APAAshiotis, G., Tsigkanos, E., Christoudias, T., & Nicolaou, M. A. (2022). AI for Air Quality: Leveraging Data Fusion for Deep Downscaling of Atmospheric Pollutants. Machine Learning for Earth Observation Workshop (MACLEAN), ECML/PKDD.
MLAAshiotis, G., et al. "AI for Air Quality: Leveraging Data Fusion for Deep Downscaling of Atmospheric Pollutants." Machine Learning for Earth Observation Workshop (MACLEAN), ECML/PKDD, 2022.
IEEEG. Ashiotis, E. Tsigkanos, T. Christoudias, and M. A. Nicolaou, "AI for Air Quality: Leveraging Data Fusion for Deep Downscaling of Atmospheric Pollutants," in Machine Learning for Earth Observation Workshop (MACLEAN), ECML/PKDD, 2022.
Efficient Learning of Multiple NLP Tasks via Collective Weight Factorization on BERT
North American Chapter of the Association for Computational Linguistics (NAACL)
BibTeX
@inproceedings{2022_Papadopoulos_NAACL,
author = {C. Papadopoulos and Y. Panagakis and M. Koubarakis and M. A. Nicolaou},
title = {Efficient Learning of Multiple NLP Tasks via Collective Weight Factorization on BERT},
booktitle = {North American Chapter of the Association for Computational Linguistics (NAACL)},
year = {2022}
}APAPapadopoulos, C., Panagakis, Y., Koubarakis, M., & Nicolaou, M. A. (2022). Efficient Learning of Multiple NLP Tasks via Collective Weight Factorization on BERT. North American Chapter of the Association for Computational Linguistics (NAACL).
MLAPapadopoulos, C., et al. "Efficient Learning of Multiple NLP Tasks via Collective Weight Factorization on BERT." North American Chapter of the Association for Computational Linguistics (NAACL), 2022.
IEEEC. Papadopoulos, Y. Panagakis, M. Koubarakis, and M. A. Nicolaou, "Efficient Learning of Multiple NLP Tasks via Collective Weight Factorization on BERT," in North American Chapter of the Association for Computational Linguistics (NAACL), 2022.
A Wavelet-based Approach for Predicting Alexithymia from Physiological Signals
International Conference on Affective Computing and Intelligent Interaction (ACII)
BibTeX
@inproceedings{2022_Filippou_ACII,
author = {V. Filippou and N. Theodosiou and M. A. Nicolaou and G. Panagiotou},
title = {A Wavelet-based Approach for Predicting Alexithymia from Physiological Signals},
booktitle = {International Conference on Affective Computing and Intelligent Interaction (ACII)},
year = {2022}
}APAFilippou, V., Theodosiou, N., Nicolaou, M. A., & Panagiotou, G. (2022). A Wavelet-based Approach for Predicting Alexithymia from Physiological Signals. International Conference on Affective Computing and Intelligent Interaction (ACII).
MLAFilippou, V., et al. "A Wavelet-based Approach for Predicting Alexithymia from Physiological Signals." International Conference on Affective Computing and Intelligent Interaction (ACII), 2022.
IEEEV. Filippou, N. Theodosiou, M. A. Nicolaou, and G. Panagiotou, "A Wavelet-based Approach for Predicting Alexithymia from Physiological Signals," in International Conference on Affective Computing and Intelligent Interaction (ACII), 2022.
Unsupervised Discovery of Semantic Concepts in Satellite Imagery with Style-based Wavelet-driven Generative Models
12th Hellenic Conference on Artificial Intelligence (SETN)
BibTeX
@inproceedings{2022_Kostagiolas_SETN,
author = {N. Kostagiolas and M. A. Nicolaou and Y. Panagakis},
title = {Unsupervised Discovery of Semantic Concepts in Satellite Imagery with Style-based Wavelet-driven Generative Models},
booktitle = {12th Hellenic Conference on Artificial Intelligence (SETN)},
year = {2022}
}APAKostagiolas, N., Nicolaou, M. A., & Panagakis, Y. (2022). Unsupervised Discovery of Semantic Concepts in Satellite Imagery with Style-based Wavelet-driven Generative Models. 12th Hellenic Conference on Artificial Intelligence (SETN).
MLAKostagiolas, N., et al. "Unsupervised Discovery of Semantic Concepts in Satellite Imagery with Style-based Wavelet-driven Generative Models." 12th Hellenic Conference on Artificial Intelligence (SETN), 2022.
IEEEN. Kostagiolas, M. A. Nicolaou, and Y. Panagakis, "Unsupervised Discovery of Semantic Concepts in Satellite Imagery with Style-based Wavelet-driven Generative Models," in 12th Hellenic Conference on Artificial Intelligence (SETN), 2022.
Deep Learning on the Sphere for Multi-model Ensembling of Significant Wave Height
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
BibTeX
@inproceedings{2022_Littardi_ICASSP,
author = {A. Littardi and A. Hildeman and M. A. Nicolaou},
title = {Deep Learning on the Sphere for Multi-model Ensembling of Significant Wave Height},
booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
year = {2022}
}APALittardi, A., Hildeman, A., & Nicolaou, M. A. (2022). Deep Learning on the Sphere for Multi-model Ensembling of Significant Wave Height. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
MLALittardi, A., et al. "Deep Learning on the Sphere for Multi-model Ensembling of Significant Wave Height." IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022.
IEEEA. Littardi, A. Hildeman, and M. A. Nicolaou, "Deep Learning on the Sphere for Multi-model Ensembling of Significant Wave Height," in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022.
Tensor Component Analysis for Interpreting the Latent Space of GANs
British Machine Vision Conference (BMVC) — oral
BibTeX
@inproceedings{2022_TCA_BMVC,
author = {J. Oldfield and M. A. Nicolaou and Y. Panagakis and I. Patras},
title = {Tensor Component Analysis for Interpreting the Latent Space of GANs},
booktitle = {British Machine Vision Conference (BMVC)},
year = {2022}
}APAOldfield, J., Nicolaou, M. A., Panagakis, Y., & Patras, I. (2022). Tensor Component Analysis for Interpreting the Latent Space of GANs. British Machine Vision Conference (BMVC).
MLAOldfield, J., et al. "Tensor Component Analysis for Interpreting the Latent Space of GANs." British Machine Vision Conference (BMVC), 2022.
IEEEJ. Oldfield, M. A. Nicolaou, Y. Panagakis, and I. Patras, "Tensor Component Analysis for Interpreting the Latent Space of GANs," in British Machine Vision Conference (BMVC), 2022.
Autohighlight: Highlight Detection in League of Legends Esports Broadcasts via Crowd-Sourced Data
Machine Learning with Applications (MLWA)
BibTeX
@article{2022_Autohighlight_MLWA,
author = {C. Ringer and M. A. Nicolaou and J. Walker},
title = {Autohighlight: Highlight Detection in League of Legends Esports Broadcasts via Crowd-Sourced Data},
journal = {Machine Learning with Applications (MLWA)},
year = {2022}
}APARinger, C., Nicolaou, M. A., & Walker, J. (2022). Autohighlight: Highlight Detection in League of Legends Esports Broadcasts via Crowd-Sourced Data. Machine Learning with Applications (MLWA).
MLARinger, C., et al. "Autohighlight: Highlight Detection in League of Legends Esports Broadcasts via Crowd-Sourced Data." Machine Learning with Applications (MLWA), 2022.
IEEEC. Ringer, M. A. Nicolaou, and J. Walker, "Autohighlight: Highlight Detection in League of Legends Esports Broadcasts via Crowd-Sourced Data," Machine Learning with Applications (MLWA), 2022.
Deep convolutional neural networks for generating atomistic configurations of multi-component macromolecules from coarse-grained models
The Journal of Chemical Physics
BibTeX
@article{2022_Christofi_JCP,
author = {E. Christofi and A. Chazirakis and C. Chrysostomou and M. A. Nicolaou and W. Li and M. Doxastakis and V. Harmandaris},
title = {Deep convolutional neural networks for generating atomistic configurations of multi-component macromolecules from coarse-grained models},
journal = {The Journal of Chemical Physics},
year = {2022}
}APAChristofi, E., Chazirakis, A., Chrysostomou, C., Nicolaou, M. A., Li, W., Doxastakis, M., & Harmandaris, V. (2022). Deep convolutional neural networks for generating atomistic configurations of multi-component macromolecules from coarse-grained models. The Journal of Chemical Physics.
MLAChristofi, E., et al. "Deep convolutional neural networks for generating atomistic configurations of multi-component macromolecules from coarse-grained models." The Journal of Chemical Physics, 2022.
IEEEE. Christofi, A. Chazirakis, C. Chrysostomou, M. A. Nicolaou, W. Li, M. Doxastakis, and V. Harmandaris, "Deep convolutional neural networks for generating atomistic configurations of multi-component macromolecules from coarse-grained models," The Journal of Chemical Physics, 2022.
Adversarial Learning of Disentangled and Generalizable Representations for Visual Attributes
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
BibTeX
@article{2022_Oldfield_TNNLS,
author = {J. Oldfield and Y. Panagakis and M. A. Nicolaou},
title = {Adversarial Learning of Disentangled and Generalizable Representations for Visual Attributes},
journal = {IEEE Transactions on Neural Networks and Learning Systems (TNNLS)},
year = {2022}
}APAOldfield, J., Panagakis, Y., & Nicolaou, M. A. (2022). Adversarial Learning of Disentangled and Generalizable Representations for Visual Attributes. IEEE Transactions on Neural Networks and Learning Systems (TNNLS).
MLAOldfield, J., et al. "Adversarial Learning of Disentangled and Generalizable Representations for Visual Attributes." IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.
IEEEJ. Oldfield, Y. Panagakis, and M. A. Nicolaou, "Adversarial Learning of Disentangled and Generalizable Representations for Visual Attributes," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.
2021
Flow-based generative models for simulating the quantum harmonic and anharmonic oscillator
Conference on Multiscale Physical and Biological Systems (STIMULATE) — Best Poster Award
BibTeX
@inproceedings{2021_Alexandrou_STIMULATE,
author = {C. Alexandrou and G. Koutsou and S. Athanasiou and M. A. Nicolaou and S. Paul},
title = {Flow-based generative models for simulating the quantum harmonic and anharmonic oscillator},
booktitle = {Conference on Multiscale Physical and Biological Systems (STIMULATE)},
year = {2021}
}APAAlexandrou, C., Koutsou, G., Athanasiou, S., Nicolaou, M. A., & Paul, S. (2021). Flow-based generative models for simulating the quantum harmonic and anharmonic oscillator. Conference on Multiscale Physical and Biological Systems (STIMULATE).
MLAAlexandrou, C., et al. "Flow-based generative models for simulating the quantum harmonic and anharmonic oscillator." Conference on Multiscale Physical and Biological Systems (STIMULATE), 2021.
IEEEC. Alexandrou, G. Koutsou, S. Athanasiou, M. A. Nicolaou, and S. Paul, "Flow-based generative models for simulating the quantum harmonic and anharmonic oscillator," in Conference on Multiscale Physical and Biological Systems (STIMULATE), 2021.
Classification of Influenza Hemagglutinin Protein Sequences using Convolutional Neural Networks
43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
BibTeX
@inproceedings{2021_Chrysostomou_EMBC,
author = {C. Chrysostomou and F. Alexandrou and M. A. Nicolaou and H. Seker},
title = {Classification of Influenza Hemagglutinin Protein Sequences using Convolutional Neural Networks},
booktitle = {43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)},
year = {2021}
}APAChrysostomou, C., Alexandrou, F., Nicolaou, M. A., & Seker, H. (2021). Classification of Influenza Hemagglutinin Protein Sequences using Convolutional Neural Networks. 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).
MLAChrysostomou, C., et al. "Classification of Influenza Hemagglutinin Protein Sequences using Convolutional Neural Networks." 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021.
IEEEC. Chrysostomou, F. Alexandrou, M. A. Nicolaou, and H. Seker, "Classification of Influenza Hemagglutinin Protein Sequences using Convolutional Neural Networks," in 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021.
Shared-space Autoencoders with Randomized Skip Connections for Building Footprint Detection with Missing Views
25th International Conference on Pattern Recognition (ICPR) Workshops — oral
BibTeX
@inproceedings{2021_Ashiotis_ICPRW,
author = {G. Ashiotis and J. Oldfield and C. Chrysostomou and T. Christoudias and M. A. Nicolaou},
title = {Shared-space Autoencoders with Randomized Skip Connections for Building Footprint Detection with Missing Views},
booktitle = {25th International Conference on Pattern Recognition (ICPR) Workshops},
year = {2021}
}APAAshiotis, G., Oldfield, J., Chrysostomou, C., Christoudias, T., & Nicolaou, M. A. (2021). Shared-space Autoencoders with Randomized Skip Connections for Building Footprint Detection with Missing Views. 25th International Conference on Pattern Recognition (ICPR) Workshops.
MLAAshiotis, G., et al. "Shared-space Autoencoders with Randomized Skip Connections for Building Footprint Detection with Missing Views." 25th International Conference on Pattern Recognition (ICPR) Workshops, 2021.
IEEEG. Ashiotis, J. Oldfield, C. Chrysostomou, T. Christoudias, and M. A. Nicolaou, "Shared-space Autoencoders with Randomized Skip Connections for Building Footprint Detection with Missing Views," in 25th International Conference on Pattern Recognition (ICPR) Workshops, 2021.
Tensor Methods in Computer Vision and Deep Learning
Proceedings of the IEEE
BibTeX
@article{2021_TMCVDL_ProcIEEE,
author = {Y. Panagakis and J. Kossaifi and G. Chrysos and J. Oldfield and M. A. Nicolaou and S. Zafeiriou and A. Anandkumar},
title = {Tensor Methods in Computer Vision and Deep Learning},
journal = {Proceedings of the IEEE},
year = {2021}
}APAPanagakis, Y., Kossaifi, J., Chrysos, G., Oldfield, J., Nicolaou, M. A., Zafeiriou, S., & Anandkumar, A. (2021). Tensor Methods in Computer Vision and Deep Learning. Proceedings of the IEEE.
MLAPanagakis, Y., et al. "Tensor Methods in Computer Vision and Deep Learning." Proceedings of the IEEE, 2021.
IEEEY. Panagakis, J. Kossaifi, G. Chrysos, J. Oldfield, M. A. Nicolaou, S. Zafeiriou, and A. Anandkumar, "Tensor Methods in Computer Vision and Deep Learning," Proceedings of the IEEE, 2021.
Mitigating Demographic Dataset Bias with Style-Based Attribute Transfer
International Journal of Computer Vision (IJCV)
BibTeX
@article{2021_Georgopoulos_IJCV,
author = {M. Georgopoulos and J. Oldfield and M. A. Nicolaou and Y. Panagakis and M. Pantic},
title = {Mitigating Demographic Dataset Bias with Style-Based Attribute Transfer},
journal = {International Journal of Computer Vision (IJCV)},
year = {2021}
}APAGeorgopoulos, M., Oldfield, J., Nicolaou, M. A., Panagakis, Y., & Pantic, M. (2021). Mitigating Demographic Dataset Bias with Style-Based Attribute Transfer. International Journal of Computer Vision (IJCV).
MLAGeorgopoulos, M., et al. "Mitigating Demographic Dataset Bias with Style-Based Attribute Transfer." International Journal of Computer Vision (IJCV), 2021.
IEEEM. Georgopoulos, J. Oldfield, M. A. Nicolaou, Y. Panagakis, and M. Pantic, "Mitigating Demographic Dataset Bias with Style-Based Attribute Transfer," International Journal of Computer Vision (IJCV), 2021.
2020
Machine Learning towards a Global Parameterisation of Atmospheric New Particle Formation and Growth
Tackling Climate Change with Machine Learning Workshop, NeurIPS
BibTeX
@inproceedings{2020_Christoudias_NeurIPSW,
author = {T. Christoudias and M. A. Nicolaou},
title = {Machine Learning towards a Global Parameterisation of Atmospheric New Particle Formation and Growth},
booktitle = {Tackling Climate Change with Machine Learning Workshop, NeurIPS},
year = {2020}
}APAChristoudias, T., & Nicolaou, M. A. (2020). Machine Learning towards a Global Parameterisation of Atmospheric New Particle Formation and Growth. Tackling Climate Change with Machine Learning Workshop, NeurIPS.
MLAChristoudias, T., and M. A. Nicolaou. "Machine Learning towards a Global Parameterisation of Atmospheric New Particle Formation and Growth." Tackling Climate Change with Machine Learning Workshop, NeurIPS, 2020.
IEEET. Christoudias, and M. A. Nicolaou, "Machine Learning towards a Global Parameterisation of Atmospheric New Particle Formation and Growth," in Tackling Climate Change with Machine Learning Workshop, NeurIPS, 2020.
TwitchChat: A Dataset for Exploring Livestream Chat
16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE)
BibTeX
@inproceedings{2020_TwitchChat_AIIDE,
author = {C. Ringer and M. A. Nicolaou and J. A. Walker},
title = {TwitchChat: A Dataset for Exploring Livestream Chat},
booktitle = {16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE)},
year = {2020}
}APARinger, C., Nicolaou, M. A., & Walker, J. A. (2020). TwitchChat: A Dataset for Exploring Livestream Chat. 16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE).
MLARinger, C., et al. "TwitchChat: A Dataset for Exploring Livestream Chat." 16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE), 2020.
IEEEC. Ringer, M. A. Nicolaou, and J. A. Walker, "TwitchChat: A Dataset for Exploring Livestream Chat," in 16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE), 2020.
Multimodel Superensembling Using Convolutional Neural Networks
Swedish Artificial Intelligence Society Workshop (SAIS) — oral
BibTeX
@inproceedings{2020_Larsson_SAIS,
author = {E. Larsson and A. Littardi and M. A. Nicolaou and L. Eriksson and W. Qazi},
title = {Multimodel Superensembling Using Convolutional Neural Networks},
booktitle = {Swedish Artificial Intelligence Society Workshop (SAIS)},
year = {2020}
}APALarsson, E., Littardi, A., Nicolaou, M. A., Eriksson, L., & Qazi, W. (2020). Multimodel Superensembling Using Convolutional Neural Networks. Swedish Artificial Intelligence Society Workshop (SAIS).
MLALarsson, E., et al. "Multimodel Superensembling Using Convolutional Neural Networks." Swedish Artificial Intelligence Society Workshop (SAIS), 2020.
IEEEE. Larsson, A. Littardi, M. A. Nicolaou, L. Eriksson, and W. Qazi, "Multimodel Superensembling Using Convolutional Neural Networks," in Swedish Artificial Intelligence Society Workshop (SAIS), 2020.
Enhancing Facial Data Diversity with Style-based Ageing
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops — oral
BibTeX
@inproceedings{2020_Georgopoulos_CVPRW,
author = {M. Georgopoulos and J. Oldfield and M. A. Nicolaou and Y. Panagakis and M. Pantic},
title = {Enhancing Facial Data Diversity with Style-based Ageing},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
year = {2020}
}APAGeorgopoulos, M., Oldfield, J., Nicolaou, M. A., Panagakis, Y., & Pantic, M. (2020). Enhancing Facial Data Diversity with Style-based Ageing. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.
MLAGeorgopoulos, M., et al. "Enhancing Facial Data Diversity with Style-based Ageing." IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020.
IEEEM. Georgopoulos, J. Oldfield, M. A. Nicolaou, Y. Panagakis, and M. Pantic, "Enhancing Facial Data Diversity with Style-based Ageing," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020.
3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation
International Journal of Computer Vision (IJCV)
BibTeX
@article{2020_3DFaceGAN_IJCV,
author = {S. Moschoglou and S. Ploumpis and M. A. Nicolaou and S. Zafeiriou},
title = {3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation},
journal = {International Journal of Computer Vision (IJCV)},
year = {2020}
}APAMoschoglou, S., Ploumpis, S., Nicolaou, M. A., & Zafeiriou, S. (2020). 3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation. International Journal of Computer Vision (IJCV).
MLAMoschoglou, S., et al. "3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation." International Journal of Computer Vision (IJCV), 2020.
IEEES. Moschoglou, S. Ploumpis, M. A. Nicolaou, and S. Zafeiriou, "3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation," International Journal of Computer Vision (IJCV), 2020.
2019
Streaming Behaviour: Livestreaming as a Paradigm for Analysis of Emotional and Social Signals
International Conference on Affective Computing and Intelligent Interaction Workshops (ACII-W)
BibTeX
@inproceedings{2019_Ringer_ACIIW,
author = {C. Ringer and M. A. Nicolaou},
title = {Streaming Behaviour: Livestreaming as a Paradigm for Analysis of Emotional and Social Signals},
booktitle = {International Conference on Affective Computing and Intelligent Interaction Workshops (ACII-W)},
year = {2019}
}APARinger, C., & Nicolaou, M. A. (2019). Streaming Behaviour: Livestreaming as a Paradigm for Analysis of Emotional and Social Signals. International Conference on Affective Computing and Intelligent Interaction Workshops (ACII-W).
MLARinger, C., and M. A. Nicolaou. "Streaming Behaviour: Livestreaming as a Paradigm for Analysis of Emotional and Social Signals." International Conference on Affective Computing and Intelligent Interaction Workshops (ACII-W), 2019.
IEEEC. Ringer, and M. A. Nicolaou, "Streaming Behaviour: Livestreaming as a Paradigm for Analysis of Emotional and Social Signals," in International Conference on Affective Computing and Intelligent Interaction Workshops (ACII-W), 2019.
Detecting Early Parkinson’s Disease from Keystroke Dynamics using the Tensor-Train Decomposition
27th European Signal Processing Conference (EUSIPCO)
BibTeX
@inproceedings{2019_Oroojeni_EUSIPCO,
author = {H. Oroojeni and J. Oldfield and M. A. Nicolaou},
title = {Detecting Early Parkinson’s Disease from Keystroke Dynamics using the Tensor-Train Decomposition},
booktitle = {27th European Signal Processing Conference (EUSIPCO)},
year = {2019}
}APAOroojeni, H., Oldfield, J., & Nicolaou, M. A. (2019). Detecting Early Parkinson’s Disease from Keystroke Dynamics using the Tensor-Train Decomposition. 27th European Signal Processing Conference (EUSIPCO).
MLAOroojeni, H., et al. "Detecting Early Parkinson’s Disease from Keystroke Dynamics using the Tensor-Train Decomposition." 27th European Signal Processing Conference (EUSIPCO), 2019.
IEEEH. Oroojeni, J. Oldfield, and M. A. Nicolaou, "Detecting Early Parkinson’s Disease from Keystroke Dynamics using the Tensor-Train Decomposition," in 27th European Signal Processing Conference (EUSIPCO), 2019.
Multimodal Joint Emotion and Game Context Recognition in League of Legends Livestreams
14th IEEE International Conference on Games (CoG) — oral
BibTeX
@inproceedings{2019_Ringer_CoG,
author = {C. Ringer and J. A. Walker and M. A. Nicolaou},
title = {Multimodal Joint Emotion and Game Context Recognition in League of Legends Livestreams},
booktitle = {14th IEEE International Conference on Games (CoG)},
year = {2019}
}APARinger, C., Walker, J. A., & Nicolaou, M. A. (2019). Multimodal Joint Emotion and Game Context Recognition in League of Legends Livestreams. 14th IEEE International Conference on Games (CoG).
MLARinger, C., et al. "Multimodal Joint Emotion and Game Context Recognition in League of Legends Livestreams." 14th IEEE International Conference on Games (CoG), 2019.
IEEEC. Ringer, J. A. Walker, and M. A. Nicolaou, "Multimodal Joint Emotion and Game Context Recognition in League of Legends Livestreams," in 14th IEEE International Conference on Games (CoG), 2019.
Time-series Clustering with Jointly Learning Deep Representations, Clusters and Temporal Boundaries
14th IEEE International Conference on Automatic Face and Gesture Recognition (FG)
BibTeX
@inproceedings{2019_Tzirakis_FG,
author = {P. Tzirakis and M. A. Nicolaou and B. Schuller and S. Zafeiriou},
title = {Time-series Clustering with Jointly Learning Deep Representations, Clusters and Temporal Boundaries},
booktitle = {14th IEEE International Conference on Automatic Face and Gesture Recognition (FG)},
year = {2019}
}APATzirakis, P., Nicolaou, M. A., Schuller, B., & Zafeiriou, S. (2019). Time-series Clustering with Jointly Learning Deep Representations, Clusters and Temporal Boundaries. 14th IEEE International Conference on Automatic Face and Gesture Recognition (FG).
MLATzirakis, P., et al. "Time-series Clustering with Jointly Learning Deep Representations, Clusters and Temporal Boundaries." 14th IEEE International Conference on Automatic Face and Gesture Recognition (FG), 2019.
IEEEP. Tzirakis, M. A. Nicolaou, B. Schuller, and S. Zafeiriou, "Time-series Clustering with Jointly Learning Deep Representations, Clusters and Temporal Boundaries," in 14th IEEE International Conference on Automatic Face and Gesture Recognition (FG), 2019.
Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond
International Journal of Computer Vision (IJCV)
BibTeX
@article{2019_AffWild_IJCV,
author = {D. Kollias and P. Tzirakis and M. A. Nicolaou},
title = {Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond},
journal = {International Journal of Computer Vision (IJCV)},
year = {2019}
}APAKollias, D., Tzirakis, P., Nicolaou, M. A., et al. (2019). Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond. International Journal of Computer Vision (IJCV).
MLAKollias, D., et al. "Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond." International Journal of Computer Vision (IJCV), 2019.
IEEED. Kollias, P. Tzirakis, M. A. Nicolaou, et al., "Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond," International Journal of Computer Vision (IJCV), 2019.
2018
Multi-Attribute Probabilistic Linear Discriminant Analysis for 3D Facial Shapes
14th Asian Conference on Computer Vision (ACCV)
BibTeX
@inproceedings{2018_Moschoglou_ACCV,
author = {S. Moschoglou and S. Ploumpis and M. A. Nicolaou and S. Zafeiriou},
title = {Multi-Attribute Probabilistic Linear Discriminant Analysis for 3D Facial Shapes},
booktitle = {14th Asian Conference on Computer Vision (ACCV)},
year = {2018}
}APAMoschoglou, S., Ploumpis, S., Nicolaou, M. A., & Zafeiriou, S. (2018). Multi-Attribute Probabilistic Linear Discriminant Analysis for 3D Facial Shapes. 14th Asian Conference on Computer Vision (ACCV).
MLAMoschoglou, S., et al. "Multi-Attribute Probabilistic Linear Discriminant Analysis for 3D Facial Shapes." 14th Asian Conference on Computer Vision (ACCV), 2018.
IEEES. Moschoglou, S. Ploumpis, M. A. Nicolaou, and S. Zafeiriou, "Multi-Attribute Probabilistic Linear Discriminant Analysis for 3D Facial Shapes," in 14th Asian Conference on Computer Vision (ACCV), 2018.
Less is More: Univariate Modelling to Detect Early Parkinson’s Disease from Keystroke Dynamics
21st International Conference on Discovery Science (DS) — oral
BibTeX
@inproceedings{2018_Milne_DS,
author = {A. Milne and K. Farrahi and M. A. Nicolaou},
title = {Less is More: Univariate Modelling to Detect Early Parkinson’s Disease from Keystroke Dynamics},
booktitle = {21st International Conference on Discovery Science (DS)},
year = {2018}
}APAMilne, A., Farrahi, K., & Nicolaou, M. A. (2018). Less is More: Univariate Modelling to Detect Early Parkinson’s Disease from Keystroke Dynamics. 21st International Conference on Discovery Science (DS).
MLAMilne, A., et al. "Less is More: Univariate Modelling to Detect Early Parkinson’s Disease from Keystroke Dynamics." 21st International Conference on Discovery Science (DS), 2018.
IEEEA. Milne, K. Farrahi, and M. A. Nicolaou, "Less is More: Univariate Modelling to Detect Early Parkinson’s Disease from Keystroke Dynamics," in 21st International Conference on Discovery Science (DS), 2018.
Streaming Behaviour: Live Streaming as a Paradigm for Multi-view Analysis of Emotional and Social Signals
International Conference on the Foundations of Digital Games (FDG) Workshops
BibTeX
@inproceedings{2018_Nicolaou_FDGW,
author = {M. A. Nicolaou and C. Ringer},
title = {Streaming Behaviour: Live Streaming as a Paradigm for Multi-view Analysis of Emotional and Social Signals},
booktitle = {International Conference on the Foundations of Digital Games (FDG) Workshops},
year = {2018}
}APANicolaou, M. A., & Ringer, C. (2018). Streaming Behaviour: Live Streaming as a Paradigm for Multi-view Analysis of Emotional and Social Signals. International Conference on the Foundations of Digital Games (FDG) Workshops.
MLANicolaou, M. A., and C. Ringer. "Streaming Behaviour: Live Streaming as a Paradigm for Multi-view Analysis of Emotional and Social Signals." International Conference on the Foundations of Digital Games (FDG) Workshops, 2018.
IEEEM. A. Nicolaou, and C. Ringer, "Streaming Behaviour: Live Streaming as a Paradigm for Multi-view Analysis of Emotional and Social Signals," in International Conference on the Foundations of Digital Games (FDG) Workshops, 2018.
Deep Unsupervised Multi-View Detection of Video Game Stream Highlights
International Conference on the Foundations of Digital Games (FDG) — oral
BibTeX
@inproceedings{2018_Ringer_FDG,
author = {C. Ringer and M. A. Nicolaou},
title = {Deep Unsupervised Multi-View Detection of Video Game Stream Highlights},
booktitle = {International Conference on the Foundations of Digital Games (FDG)},
year = {2018}
}APARinger, C., & Nicolaou, M. A. (2018). Deep Unsupervised Multi-View Detection of Video Game Stream Highlights. International Conference on the Foundations of Digital Games (FDG).
MLARinger, C., and M. A. Nicolaou. "Deep Unsupervised Multi-View Detection of Video Game Stream Highlights." International Conference on the Foundations of Digital Games (FDG), 2018.
IEEEC. Ringer, and M. A. Nicolaou, "Deep Unsupervised Multi-View Detection of Video Game Stream Highlights," in International Conference on the Foundations of Digital Games (FDG), 2018.
Deep Neuroevolution: Training Deep Neural Networks for False Alarm Detection in Intensive Care Units
26th European Signal Processing Conference (EUSIPCO)
BibTeX
@inproceedings{2018_Oroojeni_EUSIPCO,
author = {H. Oroojeni and M. M. al Rifaie and M. A. Nicolaou},
title = {Deep Neuroevolution: Training Deep Neural Networks for False Alarm Detection in Intensive Care Units},
booktitle = {26th European Signal Processing Conference (EUSIPCO)},
year = {2018}
}APAOroojeni, H., al Rifaie, M. M., & Nicolaou, M. A. (2018). Deep Neuroevolution: Training Deep Neural Networks for False Alarm Detection in Intensive Care Units. 26th European Signal Processing Conference (EUSIPCO).
MLAOroojeni, H., et al. "Deep Neuroevolution: Training Deep Neural Networks for False Alarm Detection in Intensive Care Units." 26th European Signal Processing Conference (EUSIPCO), 2018.
IEEEH. Oroojeni, M. M. al Rifaie, and M. A. Nicolaou, "Deep Neuroevolution: Training Deep Neural Networks for False Alarm Detection in Intensive Care Units," in 26th European Signal Processing Conference (EUSIPCO), 2018.
Multi-Attribute Robust Component Analysis for Facial UV Maps
IEEE Journal of Selected Topics in Signal Processing
BibTeX
@article{2018_Moschoglou_JSTSP,
author = {S. Moschoglou and E. Ververas and Y. Panagakis and M. A. Nicolaou and S. Zafeiriou},
title = {Multi-Attribute Robust Component Analysis for Facial UV Maps},
journal = {IEEE Journal of Selected Topics in Signal Processing},
year = {2018}
}APAMoschoglou, S., Ververas, E., Panagakis, Y., Nicolaou, M. A., & Zafeiriou, S. (2018). Multi-Attribute Robust Component Analysis for Facial UV Maps. IEEE Journal of Selected Topics in Signal Processing.
MLAMoschoglou, S., et al. "Multi-Attribute Robust Component Analysis for Facial UV Maps." IEEE Journal of Selected Topics in Signal Processing, 2018.
IEEES. Moschoglou, E. Ververas, Y. Panagakis, M. A. Nicolaou, and S. Zafeiriou, "Multi-Attribute Robust Component Analysis for Facial UV Maps," IEEE Journal of Selected Topics in Signal Processing, 2018.
2017
Discovering the Typing Behaviour of Parkinson’s Patients Using Topic Models
9th International Conference on Social Informatics (SocInfo)
BibTeX
@inproceedings{2017_Milne_SocInfo,
author = {A. Milne and M. A. Nicolaou and K. Farrahi},
title = {Discovering the Typing Behaviour of Parkinson’s Patients Using Topic Models},
booktitle = {9th International Conference on Social Informatics (SocInfo)},
year = {2017}
}APAMilne, A., Nicolaou, M. A., & Farrahi, K. (2017). Discovering the Typing Behaviour of Parkinson’s Patients Using Topic Models. 9th International Conference on Social Informatics (SocInfo).
MLAMilne, A., et al. "Discovering the Typing Behaviour of Parkinson’s Patients Using Topic Models." 9th International Conference on Social Informatics (SocInfo), 2017.
IEEEA. Milne, M. A. Nicolaou, and K. Farrahi, "Discovering the Typing Behaviour of Parkinson’s Patients Using Topic Models," in 9th International Conference on Social Informatics (SocInfo), 2017.
Aff-Wild: Valence and Arousal in-the-wild Challenge
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops — oral
BibTeX
@inproceedings{2017_AffWild_CVPRW,
author = {S. Zafeiriou and D. Kollias and M. A. Nicolaou and A. Papaioannou and G. Zhao and I. Kotsia},
title = {Aff-Wild: Valence and Arousal in-the-wild Challenge},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
year = {2017}
}APAZafeiriou, S., Kollias, D., Nicolaou, M. A., Papaioannou, A., Zhao, G., & Kotsia, I. (2017). Aff-Wild: Valence and Arousal in-the-wild Challenge. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.
MLAZafeiriou, S., et al. "Aff-Wild: Valence and Arousal in-the-wild Challenge." IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2017.
IEEES. Zafeiriou, D. Kollias, M. A. Nicolaou, A. Papaioannou, G. Zhao, and I. Kotsia, "Aff-Wild: Valence and Arousal in-the-wild Challenge," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2017.
Recognition of affect in the wild using deep neural networks
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops — oral
BibTeX
@inproceedings{2017_Kollias_CVPRW,
author = {D. Kollias and M. A. Nicolaou and I. Kotsia and G. Zhao and S. Zafeiriou},
title = {Recognition of affect in the wild using deep neural networks},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
year = {2017}
}APAKollias, D., Nicolaou, M. A., Kotsia, I., Zhao, G., & Zafeiriou, S. (2017). Recognition of affect in the wild using deep neural networks. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.
MLAKollias, D., et al. "Recognition of affect in the wild using deep neural networks." IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2017.
IEEED. Kollias, M. A. Nicolaou, I. Kotsia, G. Zhao, and S. Zafeiriou, "Recognition of affect in the wild using deep neural networks," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2017.
Initializing Probabilistic Linear Discriminant Analysis
European Signal Processing Conference (EUSIPCO) — oral
BibTeX
@inproceedings{2017_initPLDA_EUSIPCO,
author = {S. Moschoglou and M. A. Nicolaou and Y. Panagakis and S. Zafeiriou},
title = {Initializing Probabilistic Linear Discriminant Analysis},
booktitle = {European Signal Processing Conference (EUSIPCO)},
year = {2017}
}APAMoschoglou, S., Nicolaou, M. A., Panagakis, Y., & Zafeiriou, S. (2017). Initializing Probabilistic Linear Discriminant Analysis. European Signal Processing Conference (EUSIPCO).
MLAMoschoglou, S., et al. "Initializing Probabilistic Linear Discriminant Analysis." European Signal Processing Conference (EUSIPCO), 2017.
IEEES. Moschoglou, M. A. Nicolaou, Y. Panagakis, and S. Zafeiriou, "Initializing Probabilistic Linear Discriminant Analysis," in European Signal Processing Conference (EUSIPCO), 2017.
Dynamic Probabilistic Linear Discriminant Analysis for Video Classification
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
BibTeX
@inproceedings{2017_DPLDA_ICASSP,
author = {A. Fabris and M. A. Nicolaou and I. Kotsia and S. Zafeiriou},
title = {Dynamic Probabilistic Linear Discriminant Analysis for Video Classification},
booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
year = {2017}
}APAFabris, A., Nicolaou, M. A., Kotsia, I., & Zafeiriou, S. (2017). Dynamic Probabilistic Linear Discriminant Analysis for Video Classification. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
MLAFabris, A., et al. "Dynamic Probabilistic Linear Discriminant Analysis for Video Classification." IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017.
IEEEA. Fabris, M. A. Nicolaou, I. Kotsia, and S. Zafeiriou, "Dynamic Probabilistic Linear Discriminant Analysis for Video Classification," in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017.
End-to-End Multimodal Emotion Recognition using Deep Neural Networks
IEEE Journal of Selected Topics in Signal Processing
BibTeX
@article{2017_E2E_JSTSP,
author = {P. Tzirakis and G. Trigeorgis and M. A. Nicolaou and B. Schuller and S. Zafeiriou},
title = {End-to-End Multimodal Emotion Recognition using Deep Neural Networks},
journal = {IEEE Journal of Selected Topics in Signal Processing},
year = {2017}
}APATzirakis, P., Trigeorgis, G., Nicolaou, M. A., Schuller, B., & Zafeiriou, S. (2017). End-to-End Multimodal Emotion Recognition using Deep Neural Networks. IEEE Journal of Selected Topics in Signal Processing.
MLATzirakis, P., et al. "End-to-End Multimodal Emotion Recognition using Deep Neural Networks." IEEE Journal of Selected Topics in Signal Processing, 2017.
IEEEP. Tzirakis, G. Trigeorgis, M. A. Nicolaou, B. Schuller, and S. Zafeiriou, "End-to-End Multimodal Emotion Recognition using Deep Neural Networks," IEEE Journal of Selected Topics in Signal Processing, 2017.
Deep Canonical Time Warping for simultaneous Alignment and Representation Learning of sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
BibTeX
@article{2017_DCTW_TPAMI,
author = {G. Trigeorgis and M. A. Nicolaou and S. Zafeiriou and B. Schuller},
title = {Deep Canonical Time Warping for simultaneous Alignment and Representation Learning of sequences},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
year = {2017}
}APATrigeorgis, G., Nicolaou, M. A., Zafeiriou, S., & Schuller, B. (2017). Deep Canonical Time Warping for simultaneous Alignment and Representation Learning of sequences. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
MLATrigeorgis, G., et al. "Deep Canonical Time Warping for simultaneous Alignment and Representation Learning of sequences." IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017.
IEEEG. Trigeorgis, M. A. Nicolaou, S. Zafeiriou, and B. Schuller, "Deep Canonical Time Warping for simultaneous Alignment and Representation Learning of sequences," IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017.
2016
Facial Affect in-the-wild: A survey and a new Database
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops — oral
BibTeX
@inproceedings{2016_Zafeiriou_CVPRW,
author = {S. Zafeiriou and A. Papaioannou and I. Kotsia and M. A. Nicolaou and G. Zhao},
title = {Facial Affect in-the-wild: A survey and a new Database},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
year = {2016}
}APAZafeiriou, S., Papaioannou, A., Kotsia, I., Nicolaou, M. A., & Zhao, G. (2016). Facial Affect in-the-wild: A survey and a new Database. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.
MLAZafeiriou, S., et al. "Facial Affect in-the-wild: A survey and a new Database." IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2016.
IEEES. Zafeiriou, A. Papaioannou, I. Kotsia, M. A. Nicolaou, and G. Zhao, "Facial Affect in-the-wild: A survey and a new Database," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2016.
Deep Canonical Time Warping
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
BibTeX
@inproceedings{2016_DCTW_CVPR,
author = {G. Trigeorgis and M. A. Nicolaou and S. Zafeiriou and B. Schuller},
title = {Deep Canonical Time Warping},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2016}
}APATrigeorgis, G., Nicolaou, M. A., Zafeiriou, S., & Schuller, B. (2016). Deep Canonical Time Warping. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
MLATrigeorgis, G., et al. "Deep Canonical Time Warping." IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
IEEEG. Trigeorgis, M. A. Nicolaou, S. Zafeiriou, and B. Schuller, "Deep Canonical Time Warping," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
Mnemonic Descent Method
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
BibTeX
@inproceedings{2016_MDM_CVPR,
author = {G. Trigeorgis and P. Snape and M. A. Nicolaou and E. Antonakos and S. Zafeiriou},
title = {Mnemonic Descent Method},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2016}
}APATrigeorgis, G., Snape, P., Nicolaou, M. A., Antonakos, E., & Zafeiriou, S. (2016). Mnemonic Descent Method. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
MLATrigeorgis, G., et al. "Mnemonic Descent Method." IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
IEEEG. Trigeorgis, P. Snape, M. A. Nicolaou, E. Antonakos, and S. Zafeiriou, "Mnemonic Descent Method," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
Adieu features? End-to-End Speech Emotion Recognition using a Deep Convolutional Recurrent Network
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) — oral
BibTeX
@inproceedings{2016_Trigeorgis_ICASSP,
author = {G. Trigeorgis and F. Ringeval and R. Brueckner and E. Marchi and M. A. Nicolaou and B. Schuller and S. Zafeiriou},
title = {Adieu features? End-to-End Speech Emotion Recognition using a Deep Convolutional Recurrent Network},
booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
year = {2016}
}APATrigeorgis, G., Ringeval, F., Brueckner, R., Marchi, E., Nicolaou, M. A., Schuller, B., & Zafeiriou, S. (2016). Adieu features? End-to-End Speech Emotion Recognition using a Deep Convolutional Recurrent Network. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
MLATrigeorgis, G., et al. "Adieu features? End-to-End Speech Emotion Recognition using a Deep Convolutional Recurrent Network." IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016.
IEEEG. Trigeorgis, F. Ringeval, R. Brueckner, E. Marchi, M. A. Nicolaou, B. Schuller, and S. Zafeiriou, "Adieu features? End-to-End Speech Emotion Recognition using a Deep Convolutional Recurrent Network," in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016.
Robust Correlated and Individual Component Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
BibTeX
@article{2016_RCICA_TPAMI,
author = {Y. Panagakis and M. A. Nicolaou and S. Zafeiriou and M. Pantic},
title = {Robust Correlated and Individual Component Analysis},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
year = {2016}
}APAPanagakis, Y., Nicolaou, M. A., Zafeiriou, S., & Pantic, M. (2016). Robust Correlated and Individual Component Analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
MLAPanagakis, Y., et al. "Robust Correlated and Individual Component Analysis." IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016.
IEEEY. Panagakis, M. A. Nicolaou, S. Zafeiriou, and M. Pantic, "Robust Correlated and Individual Component Analysis," IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016.
Probabilistic Slow Features for Behaviour Analysis
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
BibTeX
@article{2016_pSFA_TNNLS,
author = {L. Zafeiriou and M. A. Nicolaou and S. Zafeiriou and S. Nikitidis and M. Pantic},
title = {Probabilistic Slow Features for Behaviour Analysis},
journal = {IEEE Transactions on Neural Networks and Learning Systems (TNNLS)},
year = {2016}
}APAZafeiriou, L., Nicolaou, M. A., Zafeiriou, S., Nikitidis, S., & Pantic, M. (2016). Probabilistic Slow Features for Behaviour Analysis. IEEE Transactions on Neural Networks and Learning Systems (TNNLS).
MLAZafeiriou, L., et al. "Probabilistic Slow Features for Behaviour Analysis." IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2016.
IEEEL. Zafeiriou, M. A. Nicolaou, S. Zafeiriou, S. Nikitidis, and M. Pantic, "Probabilistic Slow Features for Behaviour Analysis," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2016.
2015
Towards Deep Alignment of Multimodal Data
Workshop on Multimodal Learning, Neural Information Processing Systems (NIPS) — oral spotlight
BibTeX
@inproceedings{2015_Trigeorgis_NIPSW,
author = {G. Trigeorgis and M. A. Nicolaou and S. Zafeiriou and B. Schuller},
title = {Towards Deep Alignment of Multimodal Data},
booktitle = {Workshop on Multimodal Learning, Neural Information Processing Systems (NIPS) — oral spotlight},
year = {2015}
}APATrigeorgis, G., Nicolaou, M. A., Zafeiriou, S., & Schuller, B. (2015). Towards Deep Alignment of Multimodal Data. Workshop on Multimodal Learning, Neural Information Processing Systems (NIPS) — oral spotlight.
MLATrigeorgis, G., et al. "Towards Deep Alignment of Multimodal Data." Workshop on Multimodal Learning, Neural Information Processing Systems (NIPS) — oral spotlight, 2015.
IEEEG. Trigeorgis, M. A. Nicolaou, S. Zafeiriou, and B. Schuller, "Towards Deep Alignment of Multimodal Data," in Workshop on Multimodal Learning, Neural Information Processing Systems (NIPS) — oral spotlight, 2015.
2014
A Unified Framework for Probabilistic Component Analysis
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD) — oral
BibTeX
@inproceedings{2014_UPCA_ECML,
author = {M. A. Nicolaou and S. Zafeiriou and M. Pantic},
title = {A Unified Framework for Probabilistic Component Analysis},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD)},
year = {2014}
}APANicolaou, M. A., Zafeiriou, S., & Pantic, M. (2014). A Unified Framework for Probabilistic Component Analysis. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD).
MLANicolaou, M. A., et al. "A Unified Framework for Probabilistic Component Analysis." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), 2014.
IEEEM. A. Nicolaou, S. Zafeiriou, and M. Pantic, "A Unified Framework for Probabilistic Component Analysis," in European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), 2014.
Robust canonical correlation analysis: Audio-visual fusion for learning continuous interest
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) — oral
BibTeX
@inproceedings{2014_RCCA_ICASSP,
author = {M. A. Nicolaou and Y. Panagakis and S. Zafeiriou and M. Pantic},
title = {Robust canonical correlation analysis: Audio-visual fusion for learning continuous interest},
booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
year = {2014}
}APANicolaou, M. A., Panagakis, Y., Zafeiriou, S., & Pantic, M. (2014). Robust canonical correlation analysis: Audio-visual fusion for learning continuous interest. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
MLANicolaou, M. A., et al. "Robust canonical correlation analysis: Audio-visual fusion for learning continuous interest." IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014.
IEEEM. A. Nicolaou, Y. Panagakis, S. Zafeiriou, and M. Pantic, "Robust canonical correlation analysis: Audio-visual fusion for learning continuous interest," in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014.
Dynamic Probabilistic CCA for Analysis of Affective Behaviour and Fusion of Continuous Annotations
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
BibTeX
@article{2014_DPCCA_TPAMI,
author = {M. A. Nicolaou and V. Pavlovic and M. Pantic},
title = {Dynamic Probabilistic CCA for Analysis of Affective Behaviour and Fusion of Continuous Annotations},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
year = {2014}
}APANicolaou, M. A., Pavlovic, V., & Pantic, M. (2014). Dynamic Probabilistic CCA for Analysis of Affective Behaviour and Fusion of Continuous Annotations. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
MLANicolaou, M. A., et al. "Dynamic Probabilistic CCA for Analysis of Affective Behaviour and Fusion of Continuous Annotations." IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014.
IEEEM. A. Nicolaou, V. Pavlovic, and M. Pantic, "Dynamic Probabilistic CCA for Analysis of Affective Behaviour and Fusion of Continuous Annotations," IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014.
Machine Learning Methods for Social Signal Processing
Social Signal Processing, Springer-Verlag (book chapter)
BibTeX
@incollection{2014_Rudovic_SSP,
author = {O. Rudovic and M. A. Nicolaou and V. Pavlovic},
title = {Machine Learning Methods for Social Signal Processing},
booktitle = {Social Signal Processing (book chapter)},
year = {2014}
}APARudovic, O., Nicolaou, M. A., & Pavlovic, V. (2014). Machine Learning Methods for Social Signal Processing. Social Signal Processing (book chapter).
MLARudovic, O., et al. "Machine Learning Methods for Social Signal Processing." Social Signal Processing (book chapter), 2014.
IEEEO. Rudovic, M. A. Nicolaou, and V. Pavlovic, "Machine Learning Methods for Social Signal Processing," Social Signal Processing (book chapter), 2014.
2013
Robust canonical time warping for the alignment of grossly corrupted sequences
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
BibTeX
@inproceedings{2013_RCTW_CVPR,
author = {Y. Panagakis and M. A. Nicolaou and S. Zafeiriou and M. Pantic},
title = {Robust canonical time warping for the alignment of grossly corrupted sequences},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2013}
}APAPanagakis, Y., Nicolaou, M. A., Zafeiriou, S., & Pantic, M. (2013). Robust canonical time warping for the alignment of grossly corrupted sequences. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
MLAPanagakis, Y., et al. "Robust canonical time warping for the alignment of grossly corrupted sequences." IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013.
IEEEY. Panagakis, M. A. Nicolaou, S. Zafeiriou, and M. Pantic, "Robust canonical time warping for the alignment of grossly corrupted sequences," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013.
Correlated-Spaces Regression for Learning Continuous Emotion Dimensions
21st ACM International Conference on Multimedia (ACM MM)
BibTeX
@inproceedings{2013_CSR_ACMMM,
author = {M. A. Nicolaou and Y. Panagakis and S. Zafeiriou and M. Pantic},
title = {Correlated-Spaces Regression for Learning Continuous Emotion Dimensions},
booktitle = {21st ACM International Conference on Multimedia (ACM MM)},
year = {2013}
}APANicolaou, M. A., Panagakis, Y., Zafeiriou, S., & Pantic, M. (2013). Correlated-Spaces Regression for Learning Continuous Emotion Dimensions. 21st ACM International Conference on Multimedia (ACM MM).
MLANicolaou, M. A., et al. "Correlated-Spaces Regression for Learning Continuous Emotion Dimensions." 21st ACM International Conference on Multimedia (ACM MM), 2013.
IEEEM. A. Nicolaou, Y. Panagakis, S. Zafeiriou, and M. Pantic, "Correlated-Spaces Regression for Learning Continuous Emotion Dimensions," in 21st ACM International Conference on Multimedia (ACM MM), 2013.
Learning Slow Features for Behaviour Analysis
IEEE International Conference on Computer Vision (ICCV)
BibTeX
@inproceedings{2013_SFA_ICCV,
author = {L. Zafeiriou and M. A. Nicolaou and S. Zafeiriou and S. Nikitidis and M. Pantic},
title = {Learning Slow Features for Behaviour Analysis},
booktitle = {IEEE International Conference on Computer Vision (ICCV)},
year = {2013}
}APAZafeiriou, L., Nicolaou, M. A., Zafeiriou, S., Nikitidis, S., & Pantic, M. (2013). Learning Slow Features for Behaviour Analysis. IEEE International Conference on Computer Vision (ICCV).
MLAZafeiriou, L., et al. "Learning Slow Features for Behaviour Analysis." IEEE International Conference on Computer Vision (ICCV), 2013.
IEEEL. Zafeiriou, M. A. Nicolaou, S. Zafeiriou, S. Nikitidis, and M. Pantic, "Learning Slow Features for Behaviour Analysis," in IEEE International Conference on Computer Vision (ICCV), 2013.
2012
Dynamic Probabilistic CCA for Analysis of Affective Behaviour
12th European Conference on Computer Vision (ECCV)
BibTeX
@inproceedings{2012_DPCCA_ECCV,
author = {M. A. Nicolaou and V. Pavlovic and M. Pantic},
title = {Dynamic Probabilistic CCA for Analysis of Affective Behaviour},
booktitle = {12th European Conference on Computer Vision (ECCV)},
year = {2012}
}APANicolaou, M. A., Pavlovic, V., & Pantic, M. (2012). Dynamic Probabilistic CCA for Analysis of Affective Behaviour. 12th European Conference on Computer Vision (ECCV).
MLANicolaou, M. A., et al. "Dynamic Probabilistic CCA for Analysis of Affective Behaviour." 12th European Conference on Computer Vision (ECCV), 2012.
IEEEM. A. Nicolaou, V. Pavlovic, and M. Pantic, "Dynamic Probabilistic CCA for Analysis of Affective Behaviour," in 12th European Conference on Computer Vision (ECCV), 2012.
Output Associative RVM Regression for Dimensional and Continuous Emotion Prediction
Image and Vision Computing
BibTeX
@article{2012_OARVM_IVC,
author = {M. A. Nicolaou and H. Gunes and M. Pantic},
title = {Output Associative RVM Regression for Dimensional and Continuous Emotion Prediction},
journal = {Image and Vision Computing},
year = {2012}
}APANicolaou, M. A., Gunes, H., & Pantic, M. (2012). Output Associative RVM Regression for Dimensional and Continuous Emotion Prediction. Image and Vision Computing.
MLANicolaou, M. A., et al. "Output Associative RVM Regression for Dimensional and Continuous Emotion Prediction." Image and Vision Computing, 2012.
IEEEM. A. Nicolaou, H. Gunes, and M. Pantic, "Output Associative RVM Regression for Dimensional and Continuous Emotion Prediction," Image and Vision Computing, 2012.
2011
A Multi-Layer Hybrid Framework for Dimensional Emotion Classification
ACM International Conference on Multimedia (ACM MM)
BibTeX
@inproceedings{2011_Nicolaou_ACMMM,
author = {M. A. Nicolaou and H. Gunes and M. Pantic},
title = {A Multi-Layer Hybrid Framework for Dimensional Emotion Classification},
booktitle = {ACM International Conference on Multimedia (ACM MM)},
year = {2011}
}APANicolaou, M. A., Gunes, H., & Pantic, M. (2011). A Multi-Layer Hybrid Framework for Dimensional Emotion Classification. ACM International Conference on Multimedia (ACM MM).
MLANicolaou, M. A., et al. "A Multi-Layer Hybrid Framework for Dimensional Emotion Classification." ACM International Conference on Multimedia (ACM MM), 2011.
IEEEM. A. Nicolaou, H. Gunes, and M. Pantic, "A Multi-Layer Hybrid Framework for Dimensional Emotion Classification," in ACM International Conference on Multimedia (ACM MM), 2011.
Designing Frameworks for Automatic Affect Prediction and Classification in Dimensional Space
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops
BibTeX
@inproceedings{2011_Nicolaou_CVPRW,
author = {M. A. Nicolaou and H. Gunes and M. Pantic},
title = {Designing Frameworks for Automatic Affect Prediction and Classification in Dimensional Space},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
year = {2011}
}APANicolaou, M. A., Gunes, H., & Pantic, M. (2011). Designing Frameworks for Automatic Affect Prediction and Classification in Dimensional Space. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.
MLANicolaou, M. A., et al. "Designing Frameworks for Automatic Affect Prediction and Classification in Dimensional Space." IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2011.
IEEEM. A. Nicolaou, H. Gunes, and M. Pantic, "Designing Frameworks for Automatic Affect Prediction and Classification in Dimensional Space," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2011.
Output-Associative RVM Regression for Dimensional and Continuous Emotion Prediction
IEEE International Conference on Automatic Face and Gesture Recognition (FG) — Best Paper Award
BibTeX
@inproceedings{2011_OARVM_FG,
author = {M. A. Nicolaou and H. Gunes and M. Pantic},
title = {Output-Associative RVM Regression for Dimensional and Continuous Emotion Prediction},
booktitle = {IEEE International Conference on Automatic Face and Gesture Recognition (FG)},
year = {2011}
}APANicolaou, M. A., Gunes, H., & Pantic, M. (2011). Output-Associative RVM Regression for Dimensional and Continuous Emotion Prediction. IEEE International Conference on Automatic Face and Gesture Recognition (FG).
MLANicolaou, M. A., et al. "Output-Associative RVM Regression for Dimensional and Continuous Emotion Prediction." IEEE International Conference on Automatic Face and Gesture Recognition (FG), 2011.
IEEEM. A. Nicolaou, H. Gunes, and M. Pantic, "Output-Associative RVM Regression for Dimensional and Continuous Emotion Prediction," in IEEE International Conference on Automatic Face and Gesture Recognition (FG), 2011.
Continuous Prediction of Spontaneous Affect from Multiple Cues and Modalities in Valence-Arousal Space
IEEE Transactions on Affective Computing
BibTeX
@article{2011_Nicolaou_TAC,
author = {M. A. Nicolaou and H. Gunes and M. Pantic},
title = {Continuous Prediction of Spontaneous Affect from Multiple Cues and Modalities in Valence-Arousal Space},
journal = {IEEE Transactions on Affective Computing},
year = {2011}
}APANicolaou, M. A., Gunes, H., & Pantic, M. (2011). Continuous Prediction of Spontaneous Affect from Multiple Cues and Modalities in Valence-Arousal Space. IEEE Transactions on Affective Computing.
MLANicolaou, M. A., et al. "Continuous Prediction of Spontaneous Affect from Multiple Cues and Modalities in Valence-Arousal Space." IEEE Transactions on Affective Computing, 2011.
IEEEM. A. Nicolaou, H. Gunes, and M. Pantic, "Continuous Prediction of Spontaneous Affect from Multiple Cues and Modalities in Valence-Arousal Space," IEEE Transactions on Affective Computing, 2011.
Continuous Analysis of Affect from Voice and Face
Computer Analysis of Affect from Voice and Face, Springer-Verlag (book chapter)
BibTeX
@incollection{2011_Gunes_Springer,
author = {H. Gunes and M. A. Nicolaou and M. Pantic},
title = {Continuous Analysis of Affect from Voice and Face},
booktitle = {Computer Analysis of Human Behavior, Springer (book chapter)},
year = {2011}
}APAGunes, H., Nicolaou, M. A., & Pantic, M. (2011). Continuous Analysis of Affect from Voice and Face. Computer Analysis of Human Behavior, Springer (book chapter).
MLAGunes, H., et al. "Continuous Analysis of Affect from Voice and Face." Computer Analysis of Human Behavior, Springer (book chapter), 2011.
IEEEH. Gunes, M. A. Nicolaou, and M. Pantic, "Continuous Analysis of Affect from Voice and Face," Computer Analysis of Human Behavior, Springer (book chapter), 2011.
2010
Audio-visual Classification and Fusion of Spontaneous Affect Data in Likelihood Space
International Conference on Pattern Recognition (ICPR)
BibTeX
@inproceedings{2010_Nicolaou_ICPR,
author = {M. A. Nicolaou and H. Gunes and M. Pantic},
title = {Audio-visual Classification and Fusion of Spontaneous Affect Data in Likelihood Space},
booktitle = {International Conference on Pattern Recognition (ICPR)},
year = {2010}
}APANicolaou, M. A., Gunes, H., & Pantic, M. (2010). Audio-visual Classification and Fusion of Spontaneous Affect Data in Likelihood Space. International Conference on Pattern Recognition (ICPR).
MLANicolaou, M. A., et al. "Audio-visual Classification and Fusion of Spontaneous Affect Data in Likelihood Space." International Conference on Pattern Recognition (ICPR), 2010.
IEEEM. A. Nicolaou, H. Gunes, and M. Pantic, "Audio-visual Classification and Fusion of Spontaneous Affect Data in Likelihood Space," in International Conference on Pattern Recognition (ICPR), 2010.
Automatic Segmentation of Spontaneous Data using Dimensional Labels from Multiple Coders
International Workshop on Multimodal Corpora (LREC MMC)
BibTeX
@inproceedings{2010_Nicolaou_LRECMMC,
author = {M. A. Nicolaou and H. Gunes and M. Pantic},
title = {Automatic Segmentation of Spontaneous Data using Dimensional Labels from Multiple Coders},
booktitle = {International Workshop on Multimodal Corpora (LREC)},
year = {2010}
}APANicolaou, M. A., Gunes, H., & Pantic, M. (2010). Automatic Segmentation of Spontaneous Data using Dimensional Labels from Multiple Coders. International Workshop on Multimodal Corpora (LREC).
MLANicolaou, M. A., et al. "Automatic Segmentation of Spontaneous Data using Dimensional Labels from Multiple Coders." International Workshop on Multimodal Corpora (LREC), 2010.
IEEEM. A. Nicolaou, H. Gunes, and M. Pantic, "Automatic Segmentation of Spontaneous Data using Dimensional Labels from Multiple Coders," in International Workshop on Multimodal Corpora (LREC), 2010.