Bharat Singh

Reinforcement Learning · with Kumar · 2021

A researcher in the Science corpus: 1 paper; trusts 19 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 42 citations into it
• Artificial Intelligence — 30 citations into it
• Computational Theory and Mathematics — 10 citations into it
• Robotics & Control — 5 citations into it

Whom Bharat Singh trusts overall

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

1. John N. Tsitsiklis
2. Leemon C. Baird III
3. Jan Peters
4. Geoffrey J. Gordon
5. Justin A. Boyan
6. Ian H. Witten
7. Richard S. Sutton
8. Marc Peter Deisenroth
9. Vijay R. Konda
10. Erfu Yang

Papers from Bharat Singh's perspective

Ordered by how strongly the researchers Bharat Singh 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. Reinforcement Learning: An Introduction
4. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet: A large-scale hierarchical image database
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Reinforcement learning in robotic applications: a comprehensive survey (2021) — 426 citations