Quentin Berthet

Artificial Intelligence · 2018–2021

A researcher in the Science corpus: 3 papers; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 45 citations into it
• Optimization & Training — 18 citations into it
• Statistics and Probability — 13 citations into it
• Computational Theory and Mathematics — 11 citations into it
• Mathematical Optimization — 10 citations into it
• Management Science and Operations Research — 6 citations into it
• Statistical Learning Theory — 5 citations into it

Whom Quentin Berthet trusts overall

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

1. Gregory Valiant
2. Ilias Diakonikolas
3. Vaughn Climenhaga
4. Paul Valiant
5. Paul Holland
6. Sudeep Kamath
7. Diederik P. Kingma
8. Yoshua Bengio
9. Alexandre B. Tsybakov
10. Geoffrey E. Hinton

Papers from Quentin Berthet's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Gradient-based learning applied to document recognition
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. Et al
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Fast Differentiable Sorting and Ranking (2020) — 300 citations
• Efficient and Modular Implicit Differentiation (2021) — 360 citations
• Statistical Windows in Testing for the Initial Distribution of a Reversible Markov Chain (2018) — 4 citations