P. Wang

Artificial Intelligence · with Guan · 2019

A researcher in the Science corpus: 1 paper; trusts 18 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 22 citations into it
• Reinforcement Learning — 15 citations into it
• Meta & Continual Learning — 7 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it

Whom P. Wang trusts overall

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

1. Ronald J. Williams
2. Diederik P. Kingma
3. Sergey Levine
4. Chelsea Finn
5. Pieter Abbeel
6. Richard S. Sutton
7. Geoffrey E. Hinton
8. E. Todorov
9. Abhishek Gupta
10. John Schulman

Papers from P. Wang's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Et al
6. Gradient-based learning applied to document recognition
7. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
8. Attention is All you Need (Neural Information Processing Systems)
9. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
10. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning

Their papers

• Meta Reinforcement Learning with Task Embedding and Shared Policy (2019) — 56 citations