2026 Nicolas Ballas: Computer Science Researcher – H-Index, Publications & Awards

Overview

Nicolas Ballas is affiliated with Facebook in the United States. Their research primarily focuses on computer science, with a strong emphasis on computer vision and pattern recognition and artificial intelligence.

Their main fields of study include:

Computer Vision and Pattern Recognition
Artificial Intelligence
Media Technology
Electrical and Electronic Engineering
Cancer Research

Research topics covered in their work encompass:

Domain Adaptation and Few-Shot Learning
Multimodal Machine Learning Applications
Advanced Neural Network Applications
Advanced Image and Video Retrieval Techniques
Generative Adversarial Networks and Image Synthesis
Video Analysis and Summarization
Advanced Vision and Imaging

Nicolas Ballas has published extensively, with a significant number of papers appearing in the venue arXiv (Cornell University), contributing 30 publications. Other notable venues include the 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and the 2022 26th International Conference on Pattern Recognition (ICPR).

Representative recent publications include:

Static Analysis of Shape in TensorFlow Programs, 2020, arXiv (Cornell University)
DINOv2: Learning Robust Visual Features without Supervision, 2023, arXiv (Cornell University)
Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023, arXiv (Cornell University)
The Hidden Uniform Cluster Prior in Self-Supervised Learning, 2022, arXiv (Cornell University)

Frequent co-authors collaborating with Nicolas Ballas include:

Mahmoud Assran
Michael Rabbat
Ishan Misra
Piotr Bojanowski
P. Vincent

Best Publications

FitNets: Hints for Thin Deep Nets

Adriana Romero;Nicolas Ballas;Samira Ebrahimi Kahou;Antoine Chassang

2518
Citations
Theano: A Python framework for fast computation of mathematical expressions

Rami Al-Rfou;Guillaume Alain;Amjad Almahairi

2208
Citations
Describing Videos by Exploiting Temporal Structure

Li Yao;Atousa Torabi;Kyunghyun Cho;Nicolas Ballas

1234
Citations
A closer look at memorization in deep networks

Devansh Arpit;Stanisław Jastrzębski;Nicolas Ballas;David Krueger

1017
Citations
Delving Deeper into Convolutional Networks for Learning Video Representations

Nicolas Ballas;Li Yao;Chris Pal;Aaron Courville

637
Citations
Three Factors Influencing Minima in SGD

Stanislaw Jastrzebski;Zachary Kenton;Devansh Arpit;Nicolas Ballas

350
Citations
Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations.

David Krueger;Tegan Maharaj;János Kramár;Mohammad Pezeshki

289
Citations
Recurrent Batch Normalization

Tim Cooijmans;Nicolas Ballas;César Laurent;Çaglar Gülçehre

274
Citations
Stochastic Gradient Push for Distributed Deep Learning

Mahmoud Assran;Nicolas Loizou;Nicolas Ballas;Michael G. Rabbat

171
Citations
A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning

Amy Zhang;Nicolas Ballas;Joelle Pineau

131
Citations
Improved Conditional VRNNs for Video Prediction

Lluis Castrejon;Nicolas Ballas;Aaron Courville

123
Citations
Dynamic capacity networks

Amjad Almahairi;Nicolas Ballas;Tim Cooijmans;Yin Zheng

93
Citations
A Dataset and Exploration of Models for Understanding Video Data through Fill-in-the-Blank Question-Answering

Tegan Maharaj;Nicolas Ballas;Anna Rohrbach;Aaron Courville

92
Citations
Deep Nets Don't Learn via Memorization

David Krueger;Nicolas Ballas;Stanislaw Jastrzebski;Devansh Arpit

76
Citations
Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis

Thomas George;César Laurent;Xavier Bouthillier;Nicolas Ballas

73
Citations
Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism

Li Yao;Atousa Torabi;Kyunghyun Cho;Nicolas Ballas

72
Citations
Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments With Support Samples

Mahmoud Assran;Mathilde Caron;Ishan Misra;Piotr Bojanowski

66
Citations
Residual Connections Encourage Iterative Inference

Stanislaw Jastrzebski;Devansh Arpit;Nicolas Ballas;Vikas Verma

64
Citations
SloMo: Improving Communication-Efficient Distributed SGD with Slow Momentum

Jianyu Wang;Vinayak Tantia;Nicolas Ballas;Michael Rabbat

63
Citations
SlowMo: Improving Communication-Efficient Distributed SGD with Slow Momentum

Jianyu Wang;Vinayak Tantia;Nicolas Ballas;Michael Rabbat

49
Citations

Frequent Co-Authors

Yoshua Bengio University of Montreal

Aaron Courville University of Montreal

Michael Rabbat Facebook (United States)

Chris Pal Polytechnique Montréal

Kyunghyun Cho New York University

Amos Storkey University of Edinburgh

Pascal Vincent Facebook (United States)

Hugo Larochelle Google (United States)

Alexander G. Hauptmann Carnegie Mellon University

John R. Smith IBM (United States)

External Links

Personal website of Nicolas Ballas

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