Munning Wen

Reinforcement Learning · 2021

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 19 citations into it
• Artificial Intelligence — 12 citations into it

Whom Munning Wen trusts overall

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

1. John Schulman
2. Richard S. Sutton
3. Diederik P. Kingma
4. Christian Schröder de Witt

Papers from Munning Wen's perspective

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

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

Their papers

• Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning (2021) — 407 citations