Jerrick Hoang

Reinforcement Learning · 2019

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 35 citations into it
• Artificial Intelligence — 30 citations into it

Whom Jerrick Hoang trusts overall

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

1. Richard S. Sutton
2. Sergey Levine
3. John Schulman

Papers from Jerrick Hoang's perspective

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

1. Asynchronous Methods for Deep Reinforcement Learning
2. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
3. Trust Region Policy Optimization (International Conference on Machine Learning)
4. ImageNet classification with deep convolutional neural networks
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Proximal Policy Optimization Algorithms (arXiv.org)
7. Playing Atari with Deep Reinforcement Learning (arXiv.org)
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

• Benchmarking Model-Based Reinforcement Learning (2019) — 394 citations