Jun Gong

Reinforcement Learning · 2020

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 22 citations into it
• Artificial Intelligence — 17 citations into it
• Control and Systems Engineering — 7 citations into it

Whom Jun Gong trusts overall

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

1. Richard S. Sutton

Papers from Jun Gong's perspective

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

1. Human-level control through deep reinforcement learning
2. Asynchronous Methods for Deep Reinforcement Learning
3. Rectified Linear Units Improve Restricted Boltzmann Machines
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
6. ImageNet classification with deep convolutional neural networks
7. Mastering the game of Go with deep neural networks and tree search
8. Gradient-based learning applied to document recognition
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Long Short-Term Memory

Their papers

• Autonomous navigation of stratospheric balloons using reinforcement learning (2020) — 408 citations