Liang Zhao

Artificial Intelligence · with Li · 2017–2020

A researcher in the Science corpus: 7 papers; trusts 245 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 91 citations into it
• Computer Vision and Pattern Recognition — 78 citations into it
• Reinforcement Learning — 30 citations into it
• Optimization & Training — 24 citations into it
• Safety, Robustness & Interpretability — 21 citations into it
• Model Architectures — 16 citations into it
• Natural Language Processing — 12 citations into it; #4,166 of 5,688 by trust here, #3,369 by citations
• Cognitive Neuroscience — 10 citations into it

Whom Liang Zhao trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Alex Krizhevsky
4. Ilya Sutskever
5. Yoshua Bengio
6. Oriol Vinyals
7. Jimmy Ba
8. Ian J. Goodfellow
9. J. Urgen Schmidhuber
10. Yann LeCun

Who trusts Liang Zhao overall

1. Zixuan Ke
2. Jorge Armando Mendez Mendez
3. Peter Shaw
4. Xinyun Chen
5. Pengpeng Liu

Papers from Liang Zhao's perspective

Ordered by how strongly the researchers Liang Zhao 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
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

• Learning to Explore with Meta-Policy Gradient (2018) — 54 citations
• Occlusion Aware Unsupervised Learning of Optical Flow (2017) — 340 citations
• Compositional Continual Language Learning (2020) — 8 citations
• Compositional Generalization for Primitive Substitutions (2019) — 89 citations
• Interpreting and Evaluating Neural Network Robustness (2019) — 59 citations
• Compositional Language Continual Learning (2019) — 40 citations
• Interpreting Adversarial Robustness: A View from Decision Surface in Input Space (2018) — 30 citations