Weitang Liu

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 4 papers; trusts 193 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 103 citations into it; #16,827 of 35,345 by trust here, #9,641 by citations
• Reinforcement Learning — 67 citations into it
• Computer Vision and Pattern Recognition — 58 citations into it
• Generative Models — 28 citations into it
• Evaluation & Benchmarks — 18 citations into it
• Management Science and Operations Research — 16 citations into it
• Probabilistic & Bayesian Methods — 15 citations into it
• Safety, Robustness & Interpretability — 14 citations into it

Whom Weitang Liu trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Yann LeCun
4. Diederik P. Kingma
5. Yoshua Bengio
6. Kaiming He
7. Ilya Sutskever
8. Jianwen Xie
9. Antonio Torralba
10. Richard S. Sutton

Who trusts Weitang Liu overall

1. Yixuan Li
2. Rui Huang
3. Jingkang Yang
4. Yiyou Sun
5. K. J. Joseph
6. Adyasha Maharana
7. Haoqi Wang
8. Xuefeng Du
9. Francesco Tonin
10. Gyuhak Kim

Papers from Weitang Liu's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Surprising Negative Results for Generative Adversarial Tree Search (2018) — 14 citations
• Energy-based Out-of-distribution Detection (2020) — 2,043 citations
• CLUE: A Chinese Language Understanding Evaluation Benchmark (2020) — 460 citations
• Sample-Efficient Deep RL with Generative Adversarial Tree Search (2018) — 17 citations