Hugh Chen
Artificial Intelligence · 2019–2022
A researcher in the Science corpus: 4 papers; trusts 20 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 91 citations into it; #16,864 of 35,345 by trust here, #10,667 by citations
- Safety, Robustness & Interpretability — 48 citations into it; #1,423 of 2,251 by trust here, #2,110 by citations
- Computer Vision and Pattern Recognition — 20 citations into it
- Game & Decision Theory — 11 citations into it
- Natural Language Processing — 8 citations into it
- AI Ethics, Fairness & Society — 5 citations into it
Whom Hugh Chen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Lloyd S. Shapley
- Scott M. Lundberg
- Alex Krizhevsky
- Marco Ancona
- Avanti Shrikumar
- Mukund Sundararajan
- Erik Strumbelj
- Su-In Lee
- Marco Tulio Ribeiro
- Peyton Greenside
Who trusts Hugh Chen overall
- Guang Yang
- Amitojdeep Singh
- Sarah Pratt
- Plamen Parvanov Angelov
- Qinghao Ye
- Scott M. Lundberg
- Ian Covert
- Sourya Sengupta
- Rosanne Liu
- Eduardo Almeida Soares
Papers from Hugh Chen's perspective
Ordered by how strongly the researchers Hugh Chen trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Et al
- Attention is All you Need (Neural Information Processing Systems)
Their papers
- Explainable AI for Trees: From Local Explanations to Global Understanding (2019) — 385 citations
- Algorithms to estimate Shapley value feature attributions (2022) — 466 citations
- From Local Explanations to Global Understanding with Explainable AI for Trees (2020) — 8,322 citations
- Explaining Models by Propagating Shapley Values of Local Components (2019) — 139 citations