Yunyi Li

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 19 citations into it
• Safety, Robustness & Interpretability — 11 citations into it

Whom Yunyi Li trusts overall

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

1. Tong Wang
2. Trevor J. Hastie
3. Ming Yuan
4. Tianqi Chen
5. Neal Parikh

Papers from Yunyi Li's perspective

Ordered by how strongly the researchers Yunyi Li trusts endorse each paper. Same corpus, a different order for every researcher.

1. Model selection and estimation in regression with grouped variables
2. Axiomatic Attribution for Deep Networks
3. Learning Important Features Through Propagating Activation Differences
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. ImageNet classification with deep convolutional neural networks
6. XGBoost: A Scalable Tree Boosting System
7. Generalized Additive Models
8. Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead
9. Gradient-based learning applied to document recognition
10. Intelligible Models for HealthCare: Predicting Pneumonia Risk and Hospital 30-day Readmission

Their papers

• Partially Interpretable Estimators (PIE): Black-Box-Refined Interpretable Machine Learning (2021) — 5 citations