Zhi Chen

Artificial Intelligence · with Rudin · 2017–2021

A researcher in the Science corpus: 4 papers; trusts 457 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 238 citations into it; #25,582 of 35,345 by trust here, #10,566 by citations
• Computer Vision and Pattern Recognition — 127 citations into it; #15,689 of 21,575 by trust here, #8,296 by citations
• Safety, Robustness & Interpretability — 84 citations into it
• Representation & Self-Supervised Learning — 42 citations into it
• Generative Models — 38 citations into it
• Statistics and Probability — 37 citations into it
• Statistical Learning Theory — 36 citations into it
• Reinforcement Learning — 36 citations into it

Whom Zhi Chen trusts overall

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

1. Geoffrey E. Hinton
2. Cynthia Rudin
3. Kaiming He
4. Alex Krizhevsky
5. Yoshua Bengio
6. Diederik P. Kingma
7. Karen Simonyan
8. Yann LeCun
9. Ilya Sutskever
10. Ross B. Girshick

Who trusts Zhi Chen overall

1. Cynthia Rudin
2. Thomas McGrath
3. Sachit Menon
4. Chunyuan Li
5. Gesina Schwalbe

Papers from Zhi Chen's perspective

Ordered by how strongly the researchers Zhi Chen 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. 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

• Adversarial Feature Matching for Text Generation (2017) — 363 citations
• Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges (2021) — 986 citations
• Concept whitening for interpretable image recognition (2020) — 377 citations
• How to See Hidden Patterns in Metamaterials with Interpretable Machine Learning (2021) — 27 citations