Maxim Egorov

Reinforcement Learning · 2017

A researcher in the Science corpus: 1 paper; trusts 20 researchers and is trusted by 30 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 22 citations into it; #623 of 2,242 by trust here, #1,028 by citations
• Artificial Intelligence — 18 citations into it; #7,126 of 35,347 by trust here, #11,075 by citations

Whom Maxim Egorov trusts overall

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

1. John Schulman
2. Sergey Levine
3. Volodymyr Mnih
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Pieter Abbeel
7. Richard S. Sutton
8. Andrew Y. Ng
9. Diederik P. Kingma
10. Michael I. Jordan

Who trusts Maxim Egorov overall

1. Maximilian Hüttenrauch
2. Gregory Palmer
3. Pablo Hernandez-Leal
4. Shariq Iqbal
5. Jakob N. Foerster
6. Sanjeevan Ahilan
7. Yasar Sinan Nasir
8. Kun Shao
9. Yaodong Yang
10. Kaiqing Zhang

Papers from Maxim Egorov's perspective

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

Their papers

• Cooperative Multi-agent Control Using Deep Reinforcement Learning (2017) — 1,047 citations