Peng Peng
Reinforcement Learning · with Long · 2017
A researcher in the Science corpus: 2 papers; trusts 15 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Reinforcement Learning — 40 citations into it; #2,115 of 2,242 by trust here, #738 by citations
- Artificial Intelligence — 39 citations into it
- Game & Decision Theory — 11 citations into it
- Computer Vision and Pattern Recognition — 10 citations into it
- Management Science and Operations Research — 9 citations into it
- Natural Language Processing — 8 citations into it
Whom Peng Peng trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Michael L. Littman
- Ilya Sutskever
- Martin A. Dufwenberg
- Jakob N. Foerster
- Richard S. Sutton
- Yoshua Bengio
- David Silver
- Volodymyr Mnih
- Yann LeCun
Who trusts Peng Peng overall
- Jiechuan Jiang
- Marie Ossenkopf
- Tabish Rashid
- Jakob N. Foerster
- Yaodong Yang
- Pablo Hernandez-Leal
- Sai Qian Zhang
- Kun Shao
- Mackenzie Jorgensen
- Gregory Farquhar
Papers from Peng Peng's perspective
Ordered by how strongly the researchers Peng Peng trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)