Grégoire Mialon

Artificial Intelligence · 2018–2024

A researcher in the Science corpus: 6 papers; trusts 377 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 376 citations into it
• Computer Vision and Pattern Recognition — 251 citations into it
• Representation & Self-Supervised Learning — 104 citations into it
• Model Architectures — 33 citations into it
• Safety, Robustness & Interpretability — 30 citations into it
• Generative Models — 28 citations into it
• Optimization & Training — 28 citations into it
• Signal Processing — 19 citations into it

Whom Grégoire Mialon trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Yoshua Bengio
4. Alex Krizhevsky
5. Diederik P. Kingma
6. Yann LeCun
7. Ilya Sutskever
8. Ronald J. Williams
9. Karen Simonyan
10. Alex Graves

Who trusts Grégoire Mialon overall

1. Xingyao Wang
2. Zhibin Gou
3. Matthew Renze
4. Geunwoo Kim
5. Zhihong Shao
6. Theodore R. Sumers
7. Hongliang He
8. Xiaoxi Li
9. Alberto Bietti
10. Nikita Dvornik

Papers from Grégoire Mialon's perspective

Ordered by how strongly the researchers Grégoire Mialon 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Augmented Language Models: a Survey (2023) — 579 citations
• GAIA: a benchmark for General AI Assistants (2023) — 1,001 citations
• A Cookbook of Self-Supervised Learning (2023) — 398 citations
• The Llama 3 Herd of Models (2024) — 17,085 citations
• On Regularization and Robustness of Deep Neural Networks (2018) — 15 citations
• A Kernel Perspective for Regularizing Deep Neural Networks (2018) — 74 citations