Liangyuan Hu

Statistics and Probability · 2020

A researcher in the Science corpus: 1 paper; trusts 43 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 42 citations into it; #11,020 of 12,932 by trust here, #12,077 by citations
• Causal Inference & Discovery — 15 citations into it
• Artificial Intelligence — 14 citations into it
• Economics and Econometrics — 8 citations into it
• Statistical Learning Theory — 5 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it

Whom Liangyuan Hu trusts overall

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

1. Jennifer L. Hill
2. Ben B. Hansen
3. Xinkun Nie
4. Carlos M. Carvalho
5. Robert B. Gramacy
6. Hugh A. Chipman
7. James M. Robins
8. Victor Chernozhukov
9. Vincent Dorie
10. Stefan Wager

Who trusts Liangyuan Hu overall

1. Xinkun Nie

Papers from Liangyuan Hu's perspective

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

1. Regression Shrinkage and Selection via the Lasso
2. ImageNet classification with deep convolutional neural networks
3. The central role of the propensity score in observational studies for causal effects
4. Bayesian Nonparametric Modeling for Causal Inference
5. Random Forests
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. Double/debiased machine learning for treatment and structural parameters
8. Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
9. Gradient-based learning applied to document recognition
10. BART: Bayesian Additive Regression Trees

Their papers

• Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects (with Discussion) (2020) — 321 citations