A new point process model for trajectory-based events annotation. - Nicolas Ballas; Bertrand Delezoide; Françoise J. Prêteux (Image Processing: Machine Vision Applications, 2012)

CEA LIST's Participation at MediaEval 2012 Placing Task. - Adrian Popescu 001; Nicolas Ballas (MediaEval, 2012)

Trajectory signature for action recognition in video. - Nicolas Ballas; Bertrand Delezoide; Françoise J. Prêteux (ACM Multimedia, 2012)

CEA LIST at TRECVID 2012 : Semantic Indexing and instance search. - Nicolas Ballas; Benjamin Labbé; Hervé Le Borgne; Aymen Shabou (TRECVID, 2012)

IRIM at TRECVID 2012 : Semantic Indexing and Instance Search. - Nicolas Ballas; Benjamin Labbé; Aymen Shabou; Hervé Le Borgne; Philippe Gosselin; Miriam Redi; Bernard Mérialdo; Hervé Jégou; Jonathan Delhumeau; Rémi Vieux; Boris Mansencal; Jenny Benois-Pineau; et al. (TRECVID, 2012)

Space-Time Robust Representation for Action Recognition. - Nicolas Ballas; Yi Yang 001; Zhen-Zhong Lan; Bertrand Delezoide; Françoise J. Prêteux; Alexander G. Hauptmann (ICCV, 2013)

IRIM at TRECVID 2013 : Semantic Indexing and Instance Search. - Nicolas Ballas; Benjamin Labbé; Hervé Le Borgne; Philippe Gosselin; David Picard; Miriam Redi; Bernard Mérialdo; Iván González-Díaz 001; Boris Mansencal; Jenny Benois-Pineau; Stéphane Ayache; Abdelkader Hamadi; et al. (TRECVID, 2013)

Informedia@TRECVID 2013. - Zhenzhong Lan; Lu Jiang 004; Shoou-I Yu; Chenqiang Gao; Shourabh Rawat; Yang Cai 002; Shicheng Xu; Haoquan Shen; Xuanchong Li; Yipei Wang; Waito Sze; Yan Yan 002; et al. (TRECVID, 2013)

Skeleton Point Trajectories for Human Daily Activity Recognition. - Adrien Chan-Hon-Tong; Nicolas Ballas; Catherine Achard; Bertrand Delezoide; Laurent Lucat; Patrick Sayd; Françoise J. Prêteux (VISAPP (1), 2013)

Modélisation de contextes pour l'annotation sémantique de vidéos. (Context based modeling for video semantic annotation). - Nicolas Ballas (2013)

Resource Constrained Multimedia Event Detection. - Zhen-Zhong Lan; Yi Yang 001; Nicolas Ballas; Shoou-I Yu; Alexander G. Hauptmann (MMM (1), 2014)

IRIM at TRECVID 2014: Semantic Indexing and Instance Search. - Nicolas Ballas; Benjamin Labbé; Hervé Le Borgne; Philippe Gosselin; David Picard; Miriam Redi; Bernard Mérialdo; Boris Mansencal; Jenny Benois-Pineau; Stéphane Ayache; Abdelkader Hamadi; Bahjat Safadi; et al. (TRECVID, 2014)

Describing Videos by Exploiting Temporal Structure. - Li Yao; Atousa Torabi; Kyunghyun Cho; Nicolas Ballas; Christopher J. Pal; Hugo Larochelle; Aaron C. Courville (ICCV, 2015)

Large-Scale Image Mining with Flickr Groups. - Alexandru-Lucian Gînsca; Adrian Popescu 001; Hervé Le Borgne; Nicolas Ballas; Phong Vo; Ioannis Kanellos (MMM (1), 2015)

FitNets: Hints for Thin Deep Nets. - Adriana Romero; Nicolas Ballas; Samira Ebrahimi Kahou; Antoine Chassang; Carlo Gatta; Yoshua Bengio (ICLR (Poster), 2015)

Trainable performance upper bounds for image and video captioning. - Li Yao; Nicolas Ballas; KyungHyun Cho; John R. Smith; Yoshua Bengio (CoRR, 2015)

Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism. - Li Yao; Atousa Torabi; Kyunghyun Cho; Nicolas Ballas; Christopher Joseph Pal; Hugo Larochelle; Aaron C. Courville (CoRR, 2015)

Evaluation of semi-supervised learning method on action recognition. - Haoquan Shen; Yan Yan 002; Shicheng Xu; Nicolas Ballas; Wenzhi Chen (Multim. Tools Appl., 2015)

Oracle Performance for Visual Captioning. - Li Yao; Nicolas Ballas; Kyunghyun Cho; John R. Smith; Yoshua Bengio (BMVC, 2016)

Dynamic Capacity Networks. - Amjad Almahairi; Nicolas Ballas; Tim Cooijmans; Yin Zheng; Hugo Larochelle; Aaron C. Courville (ICML, 2016)

Theano: A Python framework for fast computation of mathematical expressions. - Rami Al-Rfou; Guillaume Alain; Amjad Almahairi; Christof Angermüller; Dzmitry Bahdanau; Nicolas Ballas; Frédéric Bastien; Justin Bayer; Anatoly Belikov; Alexander Belopolsky; Yoshua Bengio; Arnaud Bergeron; et al. (CoRR, 2016)

Delving Deeper into Convolutional Networks for Learning Video Representations. - Nicolas Ballas; Li Yao; Chris Pal; Aaron C. Courville (ICLR (Poster), 2016)

Recurrent Batch Normalization. - Tim Cooijmans; Nicolas Ballas; César Laurent; Aaron C. Courville (CoRR, 2016)

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. - David Krueger 001; Tegan Maharaj; János Kramár; Mohammad Pezeshki; Nicolas Ballas; Nan Rosemary Ke; Anirudh Goyal; Yoshua Bengio; Hugo Larochelle; Aaron C. Courville; Chris Pal (CoRR, 2016)

A dataset and exploration of models for understanding video data through fill-in-the-blank question-answering. - Tegan Maharaj; Nicolas Ballas; Aaron C. Courville; Christopher Joseph Pal (CoRR, 2016)

A Dataset and Exploration of Models for Understanding Video Data through Fill-in-the-Blank Question-Answering. - Tegan Maharaj; Nicolas Ballas; Anna Rohrbach; Aaron C. Courville; Christopher Joseph Pal (CVPR, 2017)

Recurrent Batch Normalization. - Tim Cooijmans; Nicolas Ballas; César Laurent; Çaglar Gülçehre; Aaron C. Courville (ICLR (Poster), 2017)

Deep Nets Don't Learn via Memorization. - David Krueger 001; Nicolas Ballas; Stanislaw Jastrzebski; Devansh Arpit; Maxinder S. Kanwal; Tegan Maharaj; Emmanuel Bengio; Asja Fischer; Aaron C. Courville (ICLR (Workshop), 2017)

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. - David Krueger 001; Tegan Maharaj; János Kramár; Mohammad Pezeshki; Nicolas Ballas; Nan Rosemary Ke; Anirudh Goyal; Yoshua Bengio; Aaron C. Courville; Christopher J. Pal (ICLR (Poster), 2017)

Recurrent Normalization Propagation. - César Laurent; Nicolas Ballas; Pascal Vincent (ICLR (Workshop), 2017)

A Closer Look at Memorization in Deep Networks. - Devansh Arpit; Stanislaw Jastrzebski; Nicolas Ballas; David Krueger 001; Emmanuel Bengio; Maxinder S. Kanwal; Tegan Maharaj; Asja Fischer; Aaron C. Courville; Yoshua Bengio; Simon Lacoste-Julien (ICML, 2017)

Three Factors Influencing Minima in SGD. - Stanislaw Jastrzebski; Zachary Kenton; Devansh Arpit; Nicolas Ballas; Asja Fischer; Yoshua Bengio; Amos J. Storkey (CoRR, 2017)

Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio. - Stanislaw Jastrzebski; Zachary Kenton; Devansh Arpit; Nicolas Ballas; Asja Fischer; Yoshua Bengio; Amos J. Storkey (ICANN (3), 2018)

Residual Connections Encourage Iterative Inference. - Stanislaw Jastrzebski; Devansh Arpit; Nicolas Ballas; Vikas Verma; Tong Che; Yoshua Bengio (ICLR (Poster), 2018)

Finding Flatter Minima with SGD. - Stanislaw Jastrzebski; Zachary Kenton; Devansh Arpit; Nicolas Ballas; Asja Fischer; Yoshua Bengio; Amos J. Storkey (ICLR (Workshop), 2018)

An Evaluation of Fisher Approximations Beyond Kronecker Factorization. - César Laurent; Thomas George; Xavier Bouthillier; Nicolas Ballas; Pascal Vincent (ICLR (Workshop), 2018)

Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis. - Thomas George; César Laurent; Xavier Bouthillier; Nicolas Ballas; Pascal Vincent (NeurIPS, 2018)

A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning. - Amy Zhang 001; Nicolas Ballas; Joelle Pineau (CoRR, 2018)

DNN's Sharpest Directions Along the SGD Trajectory. - Stanislaw Jastrzebski; Zachary Kenton; Nicolas Ballas; Asja Fischer; Yoshua Bengio; Amos J. Storkey (CoRR, 2018)

Improved Conditional VRNNs for Video Prediction. - Lluís Castrejón; Nicolas Ballas; Aaron C. Courville (ICCV, 2019)

On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length. - Stanislaw Jastrzebski; Zachary Kenton; Nicolas Ballas; Asja Fischer; Yoshua Bengio; Amos J. Storkey (ICLR (Poster), 2019)

Stochastic Gradient Push for Distributed Deep Learning. - Mahmoud Assran; Nicolas Loizou; Nicolas Ballas; Michael G. Rabbat (ICML, 2019)

Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning. - Mahmoud Assran; Joshua Romoff; Nicolas Ballas; Joelle Pineau; Mike Rabbat (NeurIPS, 2019)

Needles in Haystacks: On Classifying Tiny Objects in Large Images. - Nick Pawlowski; Suvrat Bhooshan; Nicolas Ballas; Francesco Ciompi; Ben Glocker; Michal Drozdzal (CoRR, 2019)

Proposal-Based Video Completion. - Yuan-Ting Hu; Heng Wang; Nicolas Ballas; Kristen Grauman; Alexander G. Schwing (ECCV (27), 2020)

Lookahead Converges to Stationary Points of Smooth Non-convex Functions. - Jianyu Wang; Vinayak Tantia; Nicolas Ballas; Michael G. Rabbat (ICASSP, 2020)

SlowMo: Improving Communication-Efficient Distributed SGD with Slow Momentum. - Jianyu Wang; Vinayak Tantia; Nicolas Ballas; Michael G. Rabbat (ICLR, 2020)

Recovering Petaflops in Contrastive Semi-Supervised Learning of Visual Representations. - Mahmoud Assran; Nicolas Ballas; Lluís Castrejón; Michael G. Rabbat (CoRR, 2020)

Revisiting Loss Modelling for Unstructured Pruning. - César Laurent; Camille Ballas; Thomas George; Nicolas Ballas; Pascal Vincent (CoRR, 2020)

A Closer Look at Codistillation for Distributed Training. - Shagun Sodhani; Olivier Delalleau; Mahmoud Assran; Koustuv Sinha; Nicolas Ballas; Michael G. Rabbat (CoRR, 2020)

Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples. - Mahmoud Assran; Mathilde Caron; Ishan Misra; Piotr Bojanowski; Armand Joulin; Nicolas Ballas; Michael G. Rabbat (ICCV, 2021)

Hierarchical Video Generation for Complex Data. - Lluís Castrejón; Nicolas Ballas; Aaron C. Courville (CoRR, 2021)

Trade-offs of Local SGD at Scale: An Empirical Study. - Jose Javier Gonzalez Ortiz; Jonathan Frankle; Mike Rabbat; Ari S. Morcos; Nicolas Ballas (CoRR, 2021)

VIM: Variational Independent Modules for Video Prediction. - Rim Assouel; Lluís Castrejón; Aaron C. Courville; Nicolas Ballas; Yoshua Bengio (CLeaR, 2022)

Masked Siamese Networks for Label-Efficient Learning. - Mahmoud Assran; Mathilde Caron; Ishan Misra; Piotr Bojanowski; Florian Bordes; Pascal Vincent; Armand Joulin; Mike Rabbat; Nicolas Ballas (ECCV (31), 2022)

Cascaded Video Generation for Videos In-the-Wild. - Lluís Castrejón; Nicolas Ballas; Aaron C. Courville (ICPR, 2022)

Neural Attentive Circuits. - Martin Weiss; Nasim Rahaman; Francesco Locatello; Chris Pal; Yoshua Bengio; Bernhard Schölkopf; Li Erran Li; Nicolas Ballas (NeurIPS, 2022)

BARACK: Partially Supervised Group Robustness With Guarantees. - Nimit Sharad Sohoni; Maziar Sanjabi; Nicolas Ballas; Aditya Grover; Shaoliang Nie; Hamed Firooz; Christopher Ré (CoRR, 2022)

Uniform Masking Prevails in Vision-Language Pretraining. - Siddharth Verma; Yuchen Lu; Rui Hou; Hanchao Yu; Nicolas Ballas; Madian Khabsa; Amjad Almahairi (CoRR, 2022)

Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture. - Mahmoud Assran; Quentin Duval; Ishan Misra; Piotr Bojanowski; Pascal Vincent; Michael G. Rabbat; Yann LeCun; Nicolas Ballas (CVPR, 2023)

The hidden uniform cluster prior in self-supervised learning. - Mido Assran; Randall Balestriero; Quentin Duval; Florian Bordes; Ishan Misra; Piotr Bojanowski; Pascal Vincent; Michael G. Rabbat; Nicolas Ballas (ICLR, 2023)

ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. - Badr Youbi Idrissi; Diane Bouchacourt; Randall Balestriero; Ivan Evtimov; Caner Hazirbas; Nicolas Ballas; Pascal Vincent; Michal Drozdzal; David Lopez-Paz; Mark Ibrahim (ICLR, 2023)

A Simple Recipe for Competitive Low-compute Self supervised Vision Models. - Quentin Duval; Ishan Misra; Nicolas Ballas (CoRR, 2023)

A surprisingly simple technique to control the pretraining bias for better transfer: Expand or Narrow your representation. - Florian Bordes; Samuel Lavoie; Randall Balestriero; Nicolas Ballas; Pascal Vincent (CoRR, 2023)

Predicting masked tokens in stochastic locations improves masked image modeling. - Amir Bar; Florian Bordes; Assaf Shocher; Mahmoud Assran; Pascal Vincent; Nicolas Ballas; Trevor Darrell; Amir Globerson; Yann LeCun (CoRR, 2023)

Jack of All Tasks, Master of Many: Designing General-purpose Coarse-to-Fine Vision-Language Model. - Shraman Pramanick; Guangxing Han; Rui Hou; Sayan Nag; Ser-Nam Lim; Nicolas Ballas; Qifan Wang 001; Rama Chellappa; Amjad Almahairi (CVPR, 2024)

Stochastic positional embeddings improve masked image modeling. - Amir Bar; Florian Bordes; Assaf Shocher; Mido Assran; Pascal Vincent; Nicolas Ballas; Trevor Darrell; Amir Globerson; Yann LeCun (ICML, 2024)

Modeling Caption Diversity in Contrastive Vision-Language Pretraining. - Samuel Lavoie; Polina Kirichenko; Mark Ibrahim; Mido Assran; Andrew Gordon Wilson; Aaron C. Courville; Nicolas Ballas (ICML, 2024)

Discovering Environments with XRM. - Mohammad Pezeshki; Diane Bouchacourt; Mark Ibrahim; Nicolas Ballas; Pascal Vincent; David Lopez-Paz (ICML, 2024)

Learning and Leveraging World Models in Visual Representation Learning. - Quentin Garrido; Mahmoud Assran; Nicolas Ballas; Adrien Bardes; Laurent Najman; Yann LeCun (CoRR, 2024)

Revisiting Feature Prediction for Learning Visual Representations from Video. - Adrien Bardes; Quentin Garrido; Jean Ponce; Xinlei Chen; Michael Rabbat; Yann LeCun; Mido Assran; Nicolas Ballas (Trans. Mach. Learn. Res., 2024)

DINOv2: Learning Robust Visual Features without Supervision. - Maxime Oquab; Timothée Darcet; Théo Moutakanni; Huy V. Vo; Marc Szafraniec; Vasil Khalidov; Pierre Fernandez; Daniel Haziza; Francisco Massa; Alaaeldin El-Nouby; Mido Assran; Nicolas Ballas; et al. (Trans. Mach. Learn. Res., 2024)

VEDIT: Latent Prediction Architecture For Procedural Video Representation Learning. - Han Lin; Tushar Nagarajan; Nicolas Ballas; Mido Assran; Mojtaba Komeili; Mohit Bansal; Koustuv Sinha (ICLR, 2025)

Intuitive physics understanding emerges from self-supervised pretraining on natural videos. - Quentin Garrido; Nicolas Ballas; Mahmoud Assran; Adrien Bardes; Laurent Najman; Michael Rabbat; Emmanuel Dupoux; Yann LeCun (CoRR, 2025)

Scaling Language-Free Visual Representation Learning. - David Fan; Shengbang Tong; Jiachen Zhu 002; Koustuv Sinha; Zhuang Liu 003; Xinlei Chen; Michael Rabbat; Nicolas Ballas; Yann LeCun; Amir Bar; Saining Xie (CoRR, 2025)

Locate 3D: Real-World Object Localization via Self-Supervised Learning in 3D. - Sergio Arnaud; Paul McVay; Ada Martin; Arjun Majumdar; Krishna Murthy Jatavallabhula; Phillip Thomas; Ruslan Partsey; Daniel Dugas; Abha Gejji; Alexander Sax; Vincent-Pierre Berges; Mikael Henaff; et al. (CoRR, 2025)

V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning. - Mido Assran; Adrien Bardes; David Fan; Quentin Garrido; Russell Howes; Mojtaba Komeili; Matthew J. Muckley; Ammar Rizvi; Claire Roberts; Koustuv Sinha; Artem Zholus; Sergio Arnaud; et al. (CoRR, 2025)

A Shortcut-aware Video-QA Benchmark for Physical Understanding via Minimal Video Pairs. - Benno Krojer; Mojtaba Komeili; Candace Ross; Quentin Garrido; Koustuv Sinha; Nicolas Ballas; Mahmoud Assran (CoRR, 2025)