Nicolas Ballas

Affiliations:
  • Mines ParisTech, France


According to our database1, Nicolas Ballas authored at least 76 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
DINOv2: Learning Robust Visual Features without Supervision.
Trans. Mach. Learn. Res., 2024

VEDIT: Latent Prediction Architecture For Procedural Video Representation Learning.
CoRR, 2024

Modeling Caption Diversity in Contrastive Vision-Language Pretraining.
CoRR, 2024

Revisiting Feature Prediction for Learning Visual Representations from Video.
CoRR, 2024

Learning and Leveraging World Models in Visual Representation Learning.
CoRR, 2024

Discovering Environments with XRM.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Modeling Caption Diversity in Contrastive Vision-Language Pretraining.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Stochastic positional embeddings improve masked image modeling.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Jack of All Tasks, Master of Many: Designing General-purpose Coarse-to-Fine Vision-Language Model.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Predicting masked tokens in stochastic locations improves masked image modeling.
CoRR, 2023

DINOv2: Learning Robust Visual Features without Supervision.
CoRR, 2023

A surprisingly simple technique to control the pretraining bias for better transfer: Expand or Narrow your representation.
CoRR, 2023

A Simple Recipe for Competitive Low-compute Self supervised Vision Models.
CoRR, 2023

ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

The hidden uniform cluster prior in self-supervised learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Uniform Masking Prevails in Vision-Language Pretraining.
CoRR, 2022

The Hidden Uniform Cluster Prior in Self-Supervised Learning.
CoRR, 2022

BARACK: Partially Supervised Group Robustness With Guarantees.
CoRR, 2022

Neural Attentive Circuits.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Cascaded Video Generation for Videos In-the-Wild.
Proceedings of the 26th International Conference on Pattern Recognition, 2022

Masked Siamese Networks for Label-Efficient Learning.
Proceedings of the Computer Vision - ECCV 2022, 2022

VIM: Variational Independent Modules for Video Prediction.
Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021
Trade-offs of Local SGD at Scale: An Empirical Study.
CoRR, 2021

Hierarchical Video Generation for Complex Data.
CoRR, 2021

Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
A Closer Look at Codistillation for Distributed Training.
CoRR, 2020

Revisiting Loss Modelling for Unstructured Pruning.
CoRR, 2020

Recovering Petaflops in Contrastive Semi-Supervised Learning of Visual Representations.
CoRR, 2020

SlowMo: Improving Communication-Efficient Distributed SGD with Slow Momentum.
Proceedings of the 8th International Conference on Learning Representations, 2020

Lookahead Converges to Stationary Points of Smooth Non-convex Functions.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Proposal-Based Video Completion.
Proceedings of the Computer Vision - ECCV 2020, 2020

2019
Needles in Haystacks: On Classifying Tiny Objects in Large Images.
CoRR, 2019

Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Stochastic Gradient Push for Distributed Deep Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length.
Proceedings of the 7th International Conference on Learning Representations, 2019

Improved Conditional VRNNs for Video Prediction.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018
DNN's Sharpest Directions Along the SGD Trajectory.
CoRR, 2018

A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning.
CoRR, 2018

Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

An Evaluation of Fisher Approximations Beyond Kronecker Factorization.
Proceedings of the 6th International Conference on Learning Representations, 2018

Finding Flatter Minima with SGD.
Proceedings of the 6th International Conference on Learning Representations, 2018

Residual Connections Encourage Iterative Inference.
Proceedings of the 6th International Conference on Learning Representations, 2018

Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

2017
Three Factors Influencing Minima in SGD.
CoRR, 2017

A Closer Look at Memorization in Deep Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017

Recurrent Normalization Propagation.
Proceedings of the 5th International Conference on Learning Representations, 2017

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations.
Proceedings of the 5th International Conference on Learning Representations, 2017

Deep Nets Don't Learn via Memorization.
Proceedings of the 5th International Conference on Learning Representations, 2017

Recurrent Batch Normalization.
Proceedings of the 5th International Conference on Learning Representations, 2017

A Dataset and Exploration of Models for Understanding Video Data through Fill-in-the-Blank Question-Answering.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016
A dataset and exploration of models for understanding video data through fill-in-the-blank question-answering.
CoRR, 2016

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations.
CoRR, 2016

Recurrent Batch Normalization.
CoRR, 2016

Delving Deeper into Convolutional Networks for Learning Video Representations.
Proceedings of the 4th International Conference on Learning Representations, 2016

Theano: A Python framework for fast computation of mathematical expressions.
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CoRR, 2016

Dynamic Capacity Networks.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Oracle Performance for Visual Captioning.
Proceedings of the British Machine Vision Conference 2016, 2016

2015
Evaluation of semi-supervised learning method on action recognition.
Multim. Tools Appl., 2015

Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism.
CoRR, 2015

Trainable performance upper bounds for image and video captioning.
CoRR, 2015

FitNets: Hints for Thin Deep Nets.
Proceedings of the 3rd International Conference on Learning Representations, 2015

Large-Scale Image Mining with Flickr Groups.
Proceedings of the MultiMedia Modeling - 21st International Conference, 2015

Describing Videos by Exploiting Temporal Structure.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

2014

Resource Constrained Multimedia Event Detection.
Proceedings of the MultiMedia Modeling - 20th Anniversary International Conference, 2014

2013
Modélisation de contextes pour l'annotation sémantique de vidéos. (Context based modeling for video semantic annotation).
PhD thesis, 2013

Skeleton Point Trajectories for Human Daily Activity Recognition.
Proceedings of the VISAPP 2013, 2013



Space-Time Robust Representation for Action Recognition.
Proceedings of the IEEE International Conference on Computer Vision, 2013

2012

CEA LIST at TRECVID 2012 : Semantic Indexing and instance search.
Proceedings of the 2012 TREC Video Retrieval Evaluation, 2012

Trajectory signature for action recognition in video.
Proceedings of the 20th ACM Multimedia Conference, MM '12, Nara, Japan, October 29, 2012

CEA LIST's Participation at MediaEval 2012 Placing Task.
Proceedings of the Working Notes Proceedings of the MediaEval 2012 Workshop, 2012

A new point process model for trajectory-based events annotation.
Proceedings of the Image Processing: Machine Vision Applications V, 2012


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