Vincent Dorie

Statistics and Probability · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 35 citations into it; #9,929 of 12,932 by trust here, #4,809 by citations
• Causal Inference & Discovery — 14 citations into it; #288 of 364 by trust here, #212 by citations
• Artificial Intelligence — 11 citations into it; #27,287 of 35,345 by trust here, #20,836 by citations
• Probabilistic & Bayesian Methods — 5 citations into it

Whom Vincent Dorie trusts overall

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

1. Donald B. Rubin
2. James M. Robins
3. Guido W. Imbens
4. Jennifer L. Hill
5. Robert Tibshirani
6. Thomas G. Dietterich
7. Paul R. Rosenbaum
8. M. J. van der Laan
9. Alberto Abadie
10. Peter J. Bickel

Who trusts Vincent Dorie overall

1. Liangyuan Hu
2. Cynthia Rudin
3. Sudeepa Roy
4. Katherine A. Keith
5. P. Richard Hahn
6. Liuyi Yao
7. David Edwin Carlson
8. David D. Jensen
9. Xinkun Nie
10. Jared S. Murray

Papers from Vincent Dorie's perspective

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

1. Regression Shrinkage and Selection via the Lasso
2. The central role of the propensity score in observational studies for causal effects
3. Random Forests
4. Observational Studies
5. Unified Methods for Censored Longitudinal Data and Causality
6. Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
7. Recursive partitioning for heterogeneous causal effects
8. Bayesian Nonparametric Modeling for Causal Inference
9. ImageNet classification with deep convolutional neural networks
10. On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects

Their papers

• Automated versus Do-It-Yourself Methods for Causal Inference: Lessons Learned from a Data Analysis Competition (2017) — 350 citations
• Atlantic Causal Inference Conference (ACIC) Data Analysis Challenge 2017 (2019) — 52 citations