Daniel Cervone

Statistics and Probability · 2017

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 32 citations into it; #10,144 of 12,932 by trust here, #5,481 by citations
• Causal Inference & Discovery — 13 citations into it; #287 of 364 by trust here, #212 by citations
• Artificial Intelligence — 10 citations into it; #27,282 of 35,345 by trust here, #20,836 by citations
• Probabilistic & Bayesian Methods — 5 citations into it

Whom Daniel Cervone 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. Robert Tibshirani

Who trusts Daniel Cervone overall

1. Liangyuan Hu
2. Cynthia Rudin

Papers from Daniel Cervone's perspective

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

1. The central role of the propensity score in observational studies for causal effects
2. Regression Shrinkage and Selection via the Lasso
3. Observational Studies
4. Random Forests
5. Unified Methods for Censored Longitudinal Data and Causality
6. Recursive partitioning for heterogeneous causal effects
7. Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
8. Doubly Robust Estimation in Missing Data and Causal Inference Models
9. Bayesian Nonparametric Modeling for Causal Inference
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