Philip Zhao

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 56 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 49 citations into it
• Reinforcement Learning — 44 citations into it
• Computer Vision and Pattern Recognition — 30 citations into it
• Control and Systems Engineering — 25 citations into it
• Robotics & Control — 13 citations into it
• Representation & Self-Supervised Learning — 11 citations into it

Whom Philip Zhao trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Pieter Abbeel
4. Yann LeCun
5. Andrew Y. Ng
6. Kaiming He
7. Yoshua Bengio
8. Diederik P. Kingma
9. Ilya Sutskever
10. Sergey Levine

Papers from Philip Zhao's perspective

Ordered by how strongly the researchers Philip 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. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
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. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A Framework for Efficient Robotic Manipulation (2020) — 90 citations