Matthew Soh

Reinforcement Learning · 2019

A researcher in the Science corpus: 1 paper; trusts 20 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 32 citations into it; #1,268 of 2,242 by trust here, #1,750 by citations
• Artificial Intelligence — 16 citations into it; #17,108 of 35,345 by trust here, #21,878 by citations
• Cognitive Neuroscience — 5 citations into it

Whom Matthew Soh trusts overall

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

1. Richard S. Sutton
2. Leemon C. Baird III
3. Longxin Lin
4. Martin A. Riedmiller
5. R´emi Munos
6. Andrew Barto
7. Tuomas Haarnoja
8. Csaba Szepesvari
9. Hamid Reza Maei
10. Bruno Scherrer

Who trusts Matthew Soh overall

1. Aviral Kumar
2. Nan Jiang
3. Sergey Levine

Papers from Matthew Soh's perspective

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

1. Reinforcement Learning: An Introduction
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Human-level control through deep reinforcement learning
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Diagnosing Bottlenecks in Deep Q-learning Algorithms (2019) — 153 citations