Arthur Argenson

Reinforcement Learning · 2020

A researcher in the Science corpus: 1 paper; trusts 83 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 34 citations into it; #791 of 2,242 by trust here, #1,895 by citations
• Artificial Intelligence — 30 citations into it; #9,192 of 35,345 by trust here, #25,040 by citations
• Control and Systems Engineering — 10 citations into it; #1,418 of 8,257 by trust here, #4,722 by citations
• Management Science and Operations Research — 10 citations into it
• Computational Theory and Mathematics — 6 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it

Whom Arthur Argenson trusts overall

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

1. Sergey Levine
2. Grady Williams
3. Richard S. Sutton
4. Geoffrey E. Hinton
5. Diederik P. Kingma
6. Pieter Abbeel
7. Yoshua Bengio
8. Aravind Rajeswaran
9. Alex Krizhevsky
10. John Schulman

Who trusts Arthur Argenson overall

1. Michael Janner
2. Sergey Levine
3. Qiyang Li
4. Nicklas Hansen
5. Byung-Jun Lee
6. Tianhe Yu
7. Scott Emmons
8. Cosmin Paduraru
9. Rafael Rafailov
10. Xiaolong Wang

Papers from Arthur Argenson's perspective

Ordered by how strongly the researchers Arthur Argenson 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Model-Based Offline Planning (2020) — 172 citations