Jean-Bastien Grill

Artificial Intelligence · 2019–2025

A researcher in the Science corpus: 8 papers; trusts 248 researchers and is trusted by 87 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 250 citations into it; #24,643 of 35,345 by trust here, #2,251 by citations
• Computer Vision and Pattern Recognition — 207 citations into it; #3,476 of 21,575 by trust here, #1,875 by citations
• Representation & Self-Supervised Learning — 109 citations into it; #3,010 of 3,145 by trust here, #324 by citations
• Reinforcement Learning — 58 citations into it
• Optimization & Training — 37 citations into it
• Model Architectures — 36 citations into it
• Cognitive Neuroscience — 15 citations into it
• Management Science and Operations Research — 13 citations into it

Whom Jean-Bastien Grill trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Diederik P. Kingma
5. Yoshua Bengio
6. Ross B. Girshick
7. Yann LeCun
8. Andrew Zisserman
9. Karen Simonyan
10. Ilya Sutskever

Who trusts Jean-Bastien Grill overall

1. Xinlei Chen
2. Geoffrey E. Hinton
3. Kaiming He
4. Yoshua Bengio
5. Mahmoud Assran
6. Ishan Misra
7. Trevor Darrell
8. Christoph Feichtenhofer
9. Ruslan Salakhutdinov
10. Yann LeCun

Papers from Jean-Bastien Grill's perspective

Ordered by how strongly the researchers Jean-Bastien Grill trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning (2020) — 8,797 citations
• BYOL works even without batch statistics (2020) — 131 citations
• Broaden Your Views for Self-Supervised Video Learning (2021) — 146 citations
• World Discovery Models (2019) — 28 citations
• Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning (2020) — 158 citations
• Gemma 2: Improving Open Language Models at a Practical Size (2024) — 2,206 citations
• Gemma 3 Technical Report (2025) — 1,621 citations
• MedGemma Technical Report (2025) — 365 citations