Romain Bielawski

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 49 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 21 citations into it
• Artificial Intelligence — 18 citations into it
• Representation & Self-Supervised Learning — 13 citations into it
• Multimodal Learning — 10 citations into it
• Safety, Robustness & Interpretability — 6 citations into it

Whom Romain Bielawski trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Yann LeCun
5. Yoshua Bengio
6. Tomas Mikolov
7. Ilya Sutskever
8. Alec Radford
9. Diederik P. Kingma
10. L. V. D. van der Maaten

Papers from Romain Bielawski's perspective

Ordered by how strongly the researchers Romain Bielawski trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• Does language help generalization in vision models? (2021) — 28 citations