Pin Wang
Reinforcement Learning · with Chan · 2017–2018
A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Reinforcement Learning — 9 citations into it
- Artificial Intelligence — 7 citations into it; #8,832 of 35,345 by trust here, #23,731 by citations
Whom Pin Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ahmad El Sallab
- Dylan Hadfield-Menell
- Richard S. Sutton
- Volodymyr Mnih
- Thomas B. Sheridan
- Ching-yao Chan
- Mohammed Abdou
- Sepp Hochreiter
- Stuart J. Russell
- Pieter Abbeel
Who trusts Pin Wang overall
- Szilárd Aradi
- Edouard Leurent
- Victor Talpaert
- Praveen Palanisamy
- B. R. Kiran
- Ibrahim Sobh
- Laurene Claussmann
- Sampo Kuutti
- Patrick Mannion
- Ching-yao Chan
Papers from Pin Wang's perspective
Ordered by how strongly the researchers Pin Wang trusts endorse each paper. Same corpus, a different order for every researcher.
- Long Short-Term Memory
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Human-level control through deep reinforcement learning
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Policy Gradient Methods for Reinforcement Learning with Function Approximation
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- A Reinforcement Learning Based Approach for Automated Lane Change Maneuvers (2018) — 270 citations
- Formulation of deep reinforcement learning architecture toward autonomous driving for on-ramp merge (2017) — 124 citations