Jesse Zhang

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 35 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 81 citations into it
• Reinforcement Learning — 57 citations into it
• Control and Systems Engineering — 35 citations into it
• Computer Vision and Pattern Recognition — 30 citations into it
• Robotics & Control — 15 citations into it
• Electrical and Electronic Engineering — 9 citations into it

Whom Jesse Zhang trusts overall

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

1. Geoffrey E. Hinton
2. Sergey Levine
3. Diederik P. Kingma
4. Yoshua Bengio
5. Alex Krizhevsky
6. Ilya Sutskever
7. Alex Graves
8. Richard S. Sutton
9. John Schulman
10. Yann LeCun

Papers from Jesse Zhang's perspective

Ordered by how strongly the researchers Jesse Zhang 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Learning to Synthesize Programs as Interpretable and Generalizable Policies (2021) — 96 citations
• COG: Connecting New Skills to Past Experience with Offline Reinforcement Learning (2020) — 116 citations