publications

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2024

  1. Tensor methods in Deep Learning
    In Signal Processing and Machine Learning Theory, 2024
    Y. Panagakis, J. Kossaifi, G. G. Chrysos, J. Oldfield, T. Patti, M. A. Nicolaou, A. Anandkumar, and S. Zafeiriou

2023

  1. Parts of Speech-Grounded Subspaces in Vision-Language Models
    In Advances in Neural Information Processing Systems (NeurIPS), 2023
    J. Oldfield, C. Tzelepis, Y. Panagakis, M. A. Nicolaou, and I. Patras
  2. Panda: Unsupervised Learning of Parts and Appearances in the Feature Maps of GANs
    In International Conference on Learning Representations (ICLR), 2023
    J. Oldfield, C. Tzelepis, Y. Panagakis, M. A. Nicolaou, and I. Patras
  3. Locality-preserving Directions: Interpreting the Latent Space of Satellite Image GANs
    IEEE Trans. on Geoscience and Remote Sensing Letters (GRSL), 2023
    G. Kourmouli, N. Kostagiolas, M. A. Nicolaou, and Y. Panagakis
  4. Gradient free stochastic training of ANNs, with local approximation in partitions
    Stochastic Environmental Research and Risk Assessment, 2023
    N. P. Bakas, A. Langousis, M. A. Nicolaou, and S. A. Chatzichristofis
  5. MMATR: A Lightweight Approach for Multimodal Sentiment Analysis Based on Tensor Methods
    In ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023
    P. Koromilas, M. A. Nicolaou, T. Giannakopoulos, and Y. Panagakis

2022

  1. 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
    A. Littardi, A. Hildeman, and M. A. Nicolaou
  2. Efficient Learning of Multiple NLP Tasks via Collective Weight Factorization on BERT
    Proc. of the North American Chapter of the Association for Computational Linguistics Findings (NAACL ’22), 2022
    C. C. Papadopoulos, G. Panagakis, M. Koubarakis, and M. A. Nicolaou
  3. Autohighlight: Highlight detection in League of Legends esports broadcasts via crowd-sourced data
    Machine Learning with Applications, 2022
    C. Ringer, M. A. Nicolaou, and J. Alfred Walker
  4. Unsupervised Discovery of Semantic Concepts in Satellite Imagery with Style-based Wavelet-driven Generative Models
    In Proc. of the 12th Hellenic Conference on Artificial Intelligence, 2022
    N. Kostagiolas, M. A. Nicolaou, and Y. Panagakis
  5. AI for Air Quality: Leveraging Data Fusion for Deep Downscaling of Atmospheric Pollutants
    In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), Workshop on Machine Learning for Earth Observation, 2022
    G. Ashiotis, E. Tsigkanos, T. Christoudias, and M. A. Nicolaou
  6. A Wavelet-based Approach for Multimodal Prediction of Alexithymia from Physiological Signals
    In Companion Publication of the 2022 International Conference on Multimodal Interaction, 2022
    V. Filippou, N. Theodosiou, M. A. Nicolaou, E. Constantinou, G. Panayiotou, and M. Theodorou
  7. Deep convolutional neural networks for generating atomistic configurations of multi-component macromolecules from coarse-grained models
    The Journal of Chemical Physics, 2022
    E. Christofi, A. Chazirakis, C. Chrysostomou, M. A. Nicolaou, W. Li, M. Doxastakis, and V. Harmandaris

2021

  1. Shared-space Autoencoders with Randomized Skip Connections for Building Footprint Detection with Missing Views
    In International Conference on Pattern Recognition 2020, 11th IAPR International Workshop on Pattern Recognition in Remote Sensing, 2021
    G. Ashiotis, J. Oldfield, C. Chrysostomou, T. Christoudias, and M. A. Nicolaou
  2. Adversarial learning of disentangled and generalizable representations for visual attributes
    IEEE Transactions on Neural Networks and Learning Systems, 2021
    J. Oldfield, Y. Panagakis, and M. A. Nicolaou
  3. Mitigating Demographic Bias in Facial Datasets with Style-Based Multi-Attribute Transfer
    International Journal of Computer Vision, 2021
    M. Georgopoulos, J. Oldfield, M. A. Nicolaou, Y. Panagakis, and M. Pantic
  4. Tensor methods in computer vision and deep learning
    Proceedings of the IEEE, 2021
    Y. Panagakis, J. Kossaifi, G. G. Chrysos, J. Oldfield, M. A. Nicolaou, Anima Anandkumar, and S. Zafeiriou
  5. Classification of influenza hemagglutinin protein sequences using convolutional neural networks
    In Int’l Conference of the IEEE Engineering in Medicine Biology Society (EMBC), 2021
    C. Chrysostomou, F. Alexandrou, M. A. Nicolaou, and H. Seker
  6. Tensor Component Analysis for Interpreting the Latent Space of GANs
    In British Machine Vision Conference (BMVC), 2021
    J. Oldfield, M. Georgopoulos, Y. Panagakis, M. A. Nicolaou, and I. Patras

2020

  1. 3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation
    International Journal of Computer Vision, 2020
    S. Moschoglou, S. Ploumpis, M. A. Nicolaou, A. Papaioannou, and S. Zafeiriou
  2. Enhancing facial data diversity with style-based face aging
    In Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2020
    M. Georgopoulos, J. Oldfield, M. A. Nicolaou, Y. Panagakis, and M. Pantic
  3. Multimodel Superensembling Using Convolutional Neural Networks
    In Swedish Artificial Intelligence Society Workshop, 2020
    E. Larsson, A. Littardi, M. A. Nicolaou, L. Eriksson, and Waqas Q.
  4. TwitchChat: A Dataset for Exploring Livestream Chat
    In AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2020
    C. Ringer, M. A. Nicolaou, and J. Alfred Walker
  5. Dispersive flies optimisation: modifications and application
    In Swarm Intelligence Algorithms, 2020
    M. M. al-Rifaie, H. Oroojeni MJ, and M. A. Nicolaou
  6. Machine Learning towards a Global Parameterisation of Atmospheric New Particle Formation and Growth
    In Tackling Climate Change with Machine Learning Workshop, Advances in Neural Information Processing Systems (NeurIPS), 2020
    T. Christoudias, and M. A. Nicolaou
  7. The Lagrangian remainder of Taylor’s series, distinguishes \(O(f(x))\)time complexities to polynomials or not
    arXiv preprint arXiv:2001.11811, 2020
    N. P. Bakas, E. Kosmatopoulos, M. A. Nicolaou, and S. A Chatzichristofis

2019

  1. Deep affect prediction in-the-wild: Aff-wild database and challenge, deep architectures, and beyond
    International Journal of Computer Vision, 2019
    D. Kollias, P. Tzirakis, M. A. Nicolaou, A. Papaioannou, G. Zhao, B. Schuller, I. Kotsia, and S. Zafeiriou
  2. Editorial of special issue on human behaviour analysis “in-the-Wild”
    IEEE Transactions on Affective Computing, 2019
    M. A. Nicolaou, S. Zafeiriou, I. Kotsia, G. Zhao, and J. Cohn
  3. Time-series clustering with jointly learning deep representations, clusters and temporal boundaries
    In 2019 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019), 2019
    P. Tzirakis, M. A. Nicolaou, B. Schuller, and S. Zafeiriou
  4. Multimodal joint emotion and game context recognition in league of legends livestreams
    In 2019 IEEE Conference on Games (CoG), 2019
    C. Ringer, J. Alfred Walker, and M. A. Nicolaou
  5. Detecting early Parkinson’s disease from keystroke dynamics using the tensor-train decomposition
    In 2019 27th European Signal Processing Conference (EUSIPCO), 2019
    Oroojeni MJ Hooman, J. Oldfield, and M. A. Nicolaou
  6. Streaming Behaviour: Livestreaming as a Paradigm for Analysis of Emotional and Social Signals
    In 2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW), 2019
    C. Ringer, and M. A. Nicolaou
  7. A gradient free neural network framework based on universal approximation theorem
    arXiv preprint arXiv:1909.13563, 2019
    N. P. Bakas, A. Langousis, M. A. Nicolaou, and S. A. Chatzichristofis

2018

  1. Multi-attribute robust component analysis for facial uv maps
    IEEE Journal of Selected Topics in Signal Processing, 2018
    S. Moschoglou, Evangelos Ververas, Y. Panagakis, M. A. Nicolaou, and S. Zafeiriou
  2. Deep Unsupervised Multi-View Detection of Video Game Stream Highlights
    In Int’l Conf. on the Foundations of Digital Games, 2018
    C. Ringer, and M. A. Nicolaou
  3. Less is More: Univariate Modelling to Detect Early Parkinson’s Disease from Keystroke Dynamics
    In Discovery Science 2018, 2018
    A. Milne, K. Farrahi, and M. A. Nicolaou
  4. Deep Neuroevolution: Training Deep Neural Networks for False Alarm Detection in Intensive Care Units
    In Proc. 26th European Signal Processing Conference (EUSIPCO ‘18), 2018
    H. Oroojeni, M. M. Rifaie, and M. A. Nicolaou
  5. Streaming Behaviour: Live Streaming as a Paradigm for Multi-view Analysis of Emotional and Social Signals
    In Int’l Conf. on the Foundations of Digital Games, Twitch Workshop, 2018
    M. A. Nicolaou, and C. Ringer
  6. Multi-Attribute Probabilistic Linear Discriminant Analysis for 3D Facial Shapes
    In Asian Conference on Computer Vision (ACCV), 2018
    S. Moschoglou, S. Ploumpis, M. A. Nicolaou, and S. Zafeiriou

2017

  1. Dynamic probabilistic linear discriminant analysis for video classification
    In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017
    Alessandro Fabris, M. A. Nicolaou, I. Kotsia, and S. Zafeiriou
  2. End-to-end multimodal emotion recognition using deep neural networks
    IEEE Journal of Selected Topics in Signal Processing, 2017
    P. Tzirakis, G. Trigeorgis, M. A. Nicolaou, B. Schuller, and S. Zafeiriou
  3. Deep canonical time warping for simultaneous alignment and representation learning of sequences
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017
    G. Trigeorgis, M. A. Nicolaou, B. Schuller, and S. Zafeiriou
  4. Recognition of affect in the wild using deep neural networks
    In IEEE Conference on Computer Vision and Pattern Recognition (Workshops), 2017
    D. Kollias, M. A. Nicolaou, I. Kotsia, G. Zhao, and S. Zafeiriou
  5. Aff-wild: valence and arousal’In-the-Wild’challenge
    In IEEE Conference on Computer Vision and Pattern Recognition (Workshops), 2017
    S. Zafeiriou, D. Kollias, M. A. Nicolaou, A. Papaioannou, G. Zhao, and I. Kotsia
  6. Initializing Probabilistic Linear Discriminant Analysis
    In Proc. 2017 European Signal Processing Conf. (EUSIPCO’17), 2017
    S. Moschoglou, M. A. Nicolaou, Y. Panagakis, and S. Zafeiriou
  7. Discovering the typing behaviour of Parkinson’s patients using topic models
    In Social Informatics: 9th International Conference (SocInfo), 2017
    A. Milne, M. Nicolaou, and K. Farrahi

2016

  1. 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
    G. Trigeorgis, F. Ringeval, R. Brueckner, E. Marchi, M. A. Nicolaou, B. Schuller, and S. Zafeiriou
  2. Mnemonic descent method: A recurrent process applied for end-to-end face alignment
    In IEEE Conference on Computer Vision and Pattern Recognition, 2016
    G. Trigeorgis, Patrick Snape, M. A. Nicolaou, Epameinondas Antonakos, and S. Zafeiriou
  3. Deep Canonical Time Warping
    In IEEE International Conference on Computer Vision & Pattern Recognition (CVPR), 2016
    G. Trigeorgis, M. A. Nicolaou, S. Zafeiriou, and B. W Schuller
  4. Facial Affect“In-The-Wild
    In IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2016
    S. Zafeiriou, A. Papaioannou, I. Kotsia, and G. Nicolaou
  5. Facial affect “in-the-wild”: A survey and a new database
    In 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2016
    S. Zafeiriou, A. Papaioannou, I. Kotsia, M. A. Nicolaou, and G. Zhao

2015

  1. Probabilistic slow features for behavior analysis
    IEEE Transactions on Neural Networks and Learning Systems, 2015
    L. Zafeiriou, M. A. Nicolaou, S. Zafeiriou, S. Nikitidis, and M. Pantic
  2. Robust correlated and individual component analysis
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015
    Y. Panagakis, M. A. Nicolaou, S. Zafeiriou, and M. Pantic
  3. Towards Deep Multimodal Alignment
    In NIPS Multimodal Machine Learning Workshop, 2015
    G. Trigeorgis, M. A. Nicolaou, S. Zafeiriou, and B. W. Schuller

2014

  1. Dynamic Probabilistic CCA for Analysis of Affective Behaviour and Fusion of Continuous Annotations
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014
    M. A. Nicolaou, V. Pavlovic, and M. Pantic
  2. A Unified Framework for Probabilistic Component Analysis
    ECML/PKDD 2014, 2014
    M. A. Nicolaou, S. Zafeiriou, and M. Pantic
  3. Robust canonical correlation analysis: Audio-visual fusion for learning continuous interest
    In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014
    M. A. Nicolaou, Y. Panagakis, S. Zafeiriou, and M. Pantic
  4. Machine Learning Methods for Social Signal Processing
    2014
    Ognjen Rudovic, M. A. Nicolaou, and V. Pavlovic

2013

  1. Robust canonical time warping for the alignment of grossly corrupted sequences
    In IEEE Conference on Computer Vision and Pattern Recognition, 2013
    Y. Panagakis, M. A. Nicolaou, S. Zafeiriou, and M. Pantic
  2. Correlated-spaces regression for learning continuous emotion dimensions
    In Proc. of the 21st ACM international conference on Multimedia, 2013
    M. A. Nicolaou, S. Zafeiriou, and M. Pantic
  3. Learning Slow Features for Behaviour Analysis
    In Proc. of IEEE Int’l Conf. on Computer Vision, ICCV 2013, 2013
    L. Zafeiriou, M. A. Nicolaou, S. Zafeiriou, S. Nikitidis, and M. Pantic
  4. Learning slow features for behaviour analysis
    In Proc. of the IEEE International Conference on Computer Vision, 2013
    L. Zafeiriou, M. A. Nicolaou, S. Zafeiriou, S. Nikitidis, and M. Pantic

2012

  1. Dynamic probabilistic CCA for analysis of affective behaviour
    In European Conference on Computer Vision, 2012
    M. A. Nicolaou, V. Pavlovic, and M. Pantic
  2. Output-associative RVM Regression for Dimensional and Continuous emotion prediction
    Image and Vision Computing, 2012
    M. A. Nicolaou, H. Gunes, and M. Pantic

2011

  1. Continuous Prediction of Spontaneous Affect from Multiple Cues and Modalities in Valence & Arousal Space
    Affective Computing, IEEE Transactions on, 2011
    M. A. Nicolaou, H. Gunes, and M. Pantic
  2. Continuous Analysis of Affect from Voice and Face
    Computer Analysis of Human Behavior, 2011
    H. Gunes, M. A. Nicolaou, and M. Pantic
  3. A multi-layer hybrid framework for dimensional emotion classification
    In Proc. of the 19th ACM international conference on Multimedia, 2011
    M. A. Nicolaou, H. Gunes, and M. Pantic
  4. Designing frameworks for automatic affect prediction and classification in dimensional space
    In IEEE International Conference on Computer Vision & Pattern Recognition Workshops (CVPR), 2011
    M. A. Nicolaou, H. Gunes, and M. Pantic

2010

  1. Audio-visual classification and fusion of spontaneous affective data in likelihood space
    In International Conference on Pattern Recognition (ICPR), 2010
    M. A. Nicolaou, H. Gunes, and M. Pantic
  2. Automatic Segmentation of Spontaneous Data using Dimensional Labels from Multiple Coder
    Multimodal Corpora: Advances in Capturing, Coding and Analyzing Multimodality, 2010
    M. A. Nicolaou, H. Gunes, and M. Pantic