Fast Newton active appearance models. - Jean Kossaifi; Georgios Tzimiropoulos; Maja Pantic (ICIP, 2014)

Machine learning for neuroimaging with scikit-learn. - Alexandre Abraham; Fabian Pedregosa; Michael Eickenberg; Philippe Gervais; Andreas Mueller; Jean Kossaifi; Alexandre Gramfort; Bertrand Thirion; Gaël Varoquaux (Frontiers Neuroinformatics, 2014)

The First Facial Landmark Tracking in-the-Wild Challenge: Benchmark and Results. - Jie Shen 008; Stefanos Zafeiriou; Grigoris G. Chrysos; Jean Kossaifi; Georgios Tzimiropoulos; Maja Pantic (ICCV Workshops, 2015)

Fast and exact bi-directional fitting of active appearance models. - Jean Kossaifi; Georgios Tzimiropoulos; Maja Pantic (ICIP, 2015)

TensorLy: Tensor Learning in Python. - Jean Kossaifi; Yannis Panagakis; Maja Pantic (CoRR, 2016)

Tensor Contraction Layers for Parsimonious Deep Nets. - Jean Kossaifi; Aran Khanna; Zachary C. Lipton; Tommaso Furlanello; Anima Anandkumar (CVPR Workshops, 2017)

Tensor Regression Networks. - Jean Kossaifi; Zachary C. Lipton; Aran Khanna; Tommaso Furlanello; Anima Anandkumar (CoRR, 2017)

AFEW-VA database for valence and arousal estimation in-the-wild. - Jean Kossaifi; Georgios Tzimiropoulos; Sinisa Todorovic; Maja Pantic (Image Vis. Comput., 2017)

Fast and Exact Newton and Bidirectional Fitting of Active Appearance Models. - Jean Kossaifi; Georgios Tzimiropoulos; Maja Pantic (IEEE Trans. Image Process., 2017)

GAGAN: Geometry-Aware Generative Adversarial Networks. - Jean Kossaifi; Linh Tran; Yannis Panagakis; Maja Pantic (CVPR, 2018)

Stochastic Activation Pruning for Robust Adversarial Defense. - Guneet S. Dhillon; Kamyar Azizzadenesheli; Zachary C. Lipton; Jeremy Bernstein; Jean Kossaifi; Aran Khanna; Animashree Anandkumar (ICLR (Poster), 2018)

Machine learning methods for face modelling and analysis in-the-wild. - Jean Kossaifi (2018)

T-Net: Parametrizing Fully Convolutional Nets With a Single High-Order Tensor. - Jean Kossaifi; Adrian Bulat; Georgios Tzimiropoulos; Maja Pantic (CVPR, 2019)

Valence and Arousal Estimation In-The-Wild with Tensor Methods. - Anna Mitenkova; Jean Kossaifi; Yannis Panagakis; Maja Pantic (FG, 2019)

Robust Conditional Generative Adversarial Networks. - Grigorios G. Chrysos; Jean Kossaifi; Stefanos Zafeiriou (ICLR (Poster), 2019)

SEWA DB: A Rich Database for Audio-Visual Emotion and Sentiment Research in the Wild. - Jean Kossaifi; Robert Walecki; Yannis Panagakis; Jie Shen 008; Maximilian Schmitt; Fabien Ringeval; Jing Han 010; Vedhas Pandit; Björn W. Schuller; Kam Star; Elnar Hajiyev; Maja Pantic (CoRR, 2019)

Stochastically Rank-Regularized Tensor Regression Networks. - Arinbjörn Kolbeinsson; Jean Kossaifi; Yannis Panagakis; Anima Anandkumar; Ioanna Tzoulaki; Paul M. Matthews (CoRR, 2019)

Improved training of binary networks for human pose estimation and image recognition. - Adrian Bulat; Georgios Tzimiropoulos; Jean Kossaifi; Maja Pantic (CoRR, 2019)

Matrix and tensor decompositions for training binary neural networks. - Adrian Bulat; Jean Kossaifi; Georgios Tzimiropoulos; Maja Pantic (CoRR, 2019)

Efficient N-Dimensional Convolutions via Higher-Order Factorization. - Jean Kossaifi; Adrian Bulat; Yannis Panagakis; Maja Pantic (CoRR, 2019)

Spectral Learning on Matrices and Tensors. - Majid Janzamin; Rong Ge 001; Jean Kossaifi; Anima Anandkumar (Found. Trends Mach. Learn., 2019)

Disentangling Geometry and Appearance with Regularised Geometry-Aware Generative Adversarial Networks. - Linh Tran; Jean Kossaifi; Yannis Panagakis; Maja Pantic (Int. J. Comput. Vis., 2019)

TensorLy: Tensor Learning in Python. - Jean Kossaifi; Yannis Panagakis; Anima Anandkumar; Maja Pantic (J. Mach. Learn. Res., 2019)

Incremental Multi-Domain Learning with Network Latent Tensor Factorization. - Adrian Bulat; Jean Kossaifi; Georgios Tzimiropoulos; Maja Pantic (AAAI, 2020)

Factorized Higher-Order CNNs With an Application to Spatio-Temporal Emotion Estimation. - Jean Kossaifi; Antoine Toisoul; Adrian Bulat; Yannis Panagakis; Timothy M. Hospedales; Maja Pantic (CVPR, 2020)

Toward fast and accurate human pose estimation via soft-gated skip connections. - Adrian Bulat; Jean Kossaifi; Georgios Tzimiropoulos; Maja Pantic (FG, 2020)

Speech-Driven Facial Animation Using Polynomial Fusion of Features. - Triantafyllos Kefalas; Konstantinos Vougioukas; Yannis Panagakis; Stavros Petridis; Jean Kossaifi; Maja Pantic (ICASSP, 2020)

Convolutional Tensor-Train LSTM for Spatio-Temporal Learning. - Jiahao Su; Wonmin Byeon; Jean Kossaifi; Furong Huang; Jan Kautz; Anima Anandkumar (NeurIPS, 2020)

RoCGAN: Robust Conditional GAN. - Grigorios G. Chrysos; Jean Kossaifi; Stefanos Zafeiriou (Int. J. Comput. Vis., 2020)

Tensor Regression Networks. - Jean Kossaifi; Zachary C. Lipton; Arinbjörn Kolbeinsson; Aran Khanna; Tommaso Furlanello; Anima Anandkumar (J. Mach. Learn. Res., 2020)

Defensive Tensorization. - Adrian Bulat; Jean Kossaifi; Sourav Bhattacharya; Yannis Panagakis; Timothy M. Hospedales; Georgios Tzimiropoulos; Nicholas D. Lane; Maja Pantic (BMVC, 2021)

Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning. - Anuj Mahajan; Mikayel Samvelyan; Lei Mao; Viktor Makoviychuk; Animesh Garg; Jean Kossaifi; Shimon Whiteson; Yuke Zhu; Animashree Anandkumar (ICML, 2021)

Unsupervised Controllable Generation with Self-Training. - Grigorios G. Chrysos; Jean Kossaifi; Zhiding Yu; Anima Anandkumar (IJCNN, 2021)

AugMax: Adversarial Composition of Random Augmentations for Robust Training. - Haotao Wang; Chaowei Xiao; Jean Kossaifi; Zhiding Yu; Anima Anandkumar; Zhangyang Wang (NeurIPS, 2021)

Reinforcement Learning in Factored Action Spaces using Tensor Decompositions. - Anuj Mahajan; Mikayel Samvelyan; Lei Mao; Viktor Makoviychuk; Animesh Garg; Jean Kossaifi; Shimon Whiteson; Yuke Zhu; Animashree Anandkumar (CoRR, 2021)

Tensor Dropout for Robust Learning. - Arinbjörn Kolbeinsson; Jean Kossaifi; Yannis Panagakis; Adrian Bulat; Animashree Anandkumar; Ioanna Tzoulaki; Paul M. Matthews (IEEE J. Sel. Top. Signal Process., 2021)

Estimation of continuous valence and arousal levels from faces in naturalistic conditions. - Antoine Toisoul; Jean Kossaifi; Adrian Bulat; Georgios Tzimiropoulos; Maja Pantic (Nat. Mach. Intell., 2021)

SEWA DB: A Rich Database for Audio-Visual Emotion and Sentiment Research in the Wild. - Jean Kossaifi; Robert Walecki; Yannis Panagakis; Jie Shen 008; Maximilian Schmitt; Fabien Ringeval; Jing Han 010; Vedhas Pandit; Antoine Toisoul; Björn W. Schuller; Kam Star; Elnar Hajiyev; et al. (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Tensor Methods in Computer Vision and Deep Learning. - Yannis Panagakis; Jean Kossaifi; Grigorios G. Chrysos; James Oldfield 001; Mihalis A. Nicolaou; Anima Anandkumar; Stefanos Zafeiriou (Proc. IEEE, 2021)

Augmenting Deep Classifiers with Polynomial Neural Networks. - Grigorios G. Chrysos; Markos Georgopoulos; Jiankang Deng; Jean Kossaifi; Yannis Panagakis; Anima Anandkumar (ECCV (25), 2022)

HEAT: Hardware-Efficient Automatic Tensor Decomposition for Transformer Compression. - Jiaqi Gu 002; Ben Keller; Jean Kossaifi; Anima Anandkumar; Brucek Khailany; David Z. Pan (CoRR, 2022)

Geometry-Informed Neural Operator for Large-Scale 3D PDEs. - Zongyi Li; Nikola B. Kovachki; Christopher B. Choy; Boyi Li; Jean Kossaifi; Shourya Prakash Otta; Mohammad Amin Nabian; Maximilian Stadler; Christian Hundt 002; Kamyar Azizzadenesheli; Animashree Anandkumar (NeurIPS, 2023)

Score-based Diffusion Models in Function Space. - Jae Hyun Lim 001; Nikola B. Kovachki; Ricardo Baptista; Christopher Beckham; Kamyar Azizzadenesheli; Jean Kossaifi; Vikram Voleti; Jiaming Song; Karsten Kreis; Jan Kautz; Christopher Pal; Arash Vahdat; et al. (CoRR, 2023)

Speeding up Fourier Neural Operators via Mixed Precision. - Colin White; Renbo Tu; Jean Kossaifi; Gennady Pekhimenko; Kamyar Azizzadenesheli; Anima Anandkumar (CoRR, 2023)

Neural Operators for Accelerating Scientific Simulations and Design. - Kamyar Azizzadenesheli; Nikola B. Kovachki; Zongyi Li; Miguel Liu-Schiaffini; Jean Kossaifi; Anima Anandkumar (CoRR, 2023)

Quantum Goemans-Williamson Algorithm with the Hadamard Test and Approximate Amplitude Constraints. - Taylor L. Patti; Jean Kossaifi; Anima Anandkumar; Susanne F. Yelin (Quantum, 2023)

nilearn. - Nilearn Contributors; Ahmad Chamma; Aina Frau-Pascual; Alex Rothberg; Alexandre Abadie; Alexandre Abraham; Alexandre Gramfort; Alexandre Savio; Alexandre Cionca; Alexis Thual; Alisha Kodibagkar; Amadeus Kanaan; et al. (Zenodo, 2023)

Guaranteed Approximation Bounds for Mixed-Precision Neural Operators. - Renbo Tu; Colin White; Jean Kossaifi; Boris Bonev; Gennady Pekhimenko; Kamyar Azizzadenesheli; Anima Anandkumar (ICLR, 2024)

Equivariant Graph Neural Operator for Modeling 3D Dynamics. - Minkai Xu; Jiaqi Han; Aaron Lou; Jean Kossaifi; Arvind Ramanathan; Kamyar Azizzadenesheli; Jure Leskovec; Stefano Ermon; Anima Anandkumar (ICML, 2024)

Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs. - Md. Ashiqur Rahman; Robert Joseph George; Mogab Elleithy; Daniel V. Leibovici; Zongyi Li; Boris Bonev; Colin White; Julius Berner; Raymond A. Yeh; Jean Kossaifi; Kamyar Azizzadenesheli; Animashree Anandkumar (NeurIPS, 2024)

Fourier Neural Operators for Learning Dynamics in Quantum Spin Systems. - Freya Shah; Taylor L. Patti; Julius Berner; Bahareh Tolooshams; Jean Kossaifi; Anima Anandkumar (CoRR, 2024)

Exploring the design space of deep-learning-based weather forecasting systems. - Shoaib Ahmed Siddiqui; Jean Kossaifi; Boris Bonev; Christopher B. Choy; Jan Kautz; David Krueger 001; Kamyar Azizzadenesheli (CoRR, 2024)

A Library for Learning Neural Operators. - Jean Kossaifi; Nikola B. Kovachki; Zongyi Li; David Pitt; Miguel Liu-Schiaffini; Robert Joseph George; Boris Bonev; Kamyar Azizzadenesheli; Julius Berner; Anima Anandkumar (CoRR, 2024)

Incremental Spatial and Spectral Learning of Neural Operators for Solving Large-Scale PDEs. - Robert Joseph George; Jiawei Zhao; Jean Kossaifi; Zongyi Li; Anima Anandkumar (Trans. Mach. Learn. Res., 2024)

Multi-Grid Tensorized Fourier Neural Operator for High- Resolution PDEs. - Jean Kossaifi; Nikola Borislavov Kovachki; Kamyar Azizzadenesheli; Anima Anandkumar (Trans. Mach. Learn. Res., 2024)

nilearn. - Nilearn Contributors; Ahmad Chamma; Aina Frau-Pascual; Alex Rothberg; Alexandre Abadie; Alexandre Abraham; Alexandre Gramfort; Alexandre Savio; Alexandre Cionca; Alexis Thual; Alisha Kodibagkar; Amadeus Kanaan; et al. (Zenodo, 2024)

nilearn. - Nilearn Contributors; Ahmad Chamma; Aina Frau-Pascual; Alex Rothberg; Alexandre Abadie; Alexandre Abraham; Alexandre Gramfort; Alexandre Savio; Alexandre Cionca; Alexis Thual; Alisha Kodibagkar; Amadeus Kanaan; et al. (Zenodo, 2024)

nilearn. - Nilearn Contributors; Ahmad Chamma; Aina Frau-Pascual; Alex Rothberg; Alexandre Abadie; Alexandre Abraham; Alexandre Gramfort; Alexandre Savio; Alexandre Cionca; Alexandre Sayal; Alexis Thual; Alisha Kodibagkar; et al. (Zenodo, 2024)

nilearn. - Nilearn Contributors; Ahmad Chamma; Aina Frau-Pascual; Alex Rothberg; Alexandre Abadie; Alexandre Abraham; Alexandre Gramfort; Alexandre Savio; Alexandre Cionca; Alexandre Sayal; Alexis Thual; Alisha Kodibagkar; et al. (Zenodo, 2024)

nilearn. - Nilearn Contributors; Ahmad Chamma; Aina Frau-Pascual; Alex Rothberg; Alexandre Abadie; Alexandre Abraham; Alexandre Gramfort; Alexandre Savio; Alexandre Cionca; Alexandre Sayal; Alexis Thual; Alisha Kodibagkar; et al. (Zenodo, 2024)

nilearn. - Nilearn Contributors; Ahmad Chamma; Aina Frau-Pascual; Alex Rothberg; Alexandre Abadie; Alexandre Abraham; Alexandre Gramfort; Alexandre Savio; Alexandre Cionca; Alexandre Sayal; Alexis Thual; Alisha Kodibagkar; et al. (Zenodo, 2025)

nilearn. - Nilearn Contributors; Ahmad Chamma; Aina Frau-Pascual; Alex Rothberg; Alexandre Abadie; Alexandre Abraham; Alexandre Gramfort; Alexandre Savio; Alexandre Cionca; Alexandre Sayal; Alexis Thual; Alisha Kodibagkar; et al. (Zenodo, 2025)

Tensor-GaLore: Memory-Efficient Training via Gradient Tensor Decomposition. - Robert Joseph George; David Pitt; Jiawei Zhao; Jean Kossaifi; Cheng Luo; Yuandong Tian; Anima Anandkumar (CoRR, 2025)

Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction. - Christopher B. Choy; Alexey Kamenev; Jean Kossaifi; Max Rietmann; Jan Kautz; Kamyar Azizzadenesheli (CoRR, 2025)

Enabling Automatic Differentiation with Mollified Graph Neural Operators. - Ryan Y. Lin; Julius Berner; Valentin Duruisseaux; David Pitt; Daniel V. Leibovici; Jean Kossaifi; Kamyar Azizzadenesheli; Anima Anandkumar (CoRR, 2025)

Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning. - Julius Berner; Miguel Liu-Schiaffini; Jean Kossaifi; Valentin Duruisseaux; Boris Bonev; Kamyar Azizzadenesheli; Anima Anandkumar (CoRR, 2025)

FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale. - Boris Bonev; Thorsten Kurth; Ankur Mahesh; Mauro Bisson; Jean Kossaifi; Karthik Kashinath; Anima Anandkumar; William D. Collins; Michael S. Pritchard; Alexander Keller (CoRR, 2025)