David T. Arbour

Statistics and Probability · 2013–2021

A researcher in the Science corpus: 2 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 24 citations into it
• Artificial Intelligence — 13 citations into it
• Causal Inference & Discovery — 5 citations into it

Whom David T. Arbour trusts overall

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

1. Alexandre B. Tsybakov
2. James M. Robins
3. Tom L. Burr
4. Christopher Meek
5. Steven R. Howard
6. Aaditya Ramdas
7. Patrik O. Hoyer
8. D. Scharfstein
9. Jan Peters
10. Glenn Shafer

Papers from David T. Arbour's perspective

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

1. Causation, Prediction, and Search
2. Causality : Models , Reasoning , and Inference
3. Nonlinear causal discovery with additive noise models
4. Adjusting for Nonignorable Drop-Out Using Semiparametric Nonresponse Models
5. A Linear Non-Gaussian Acyclic Model for Causal Discovery
6. Estimation of Regression Coefficients When Some Regressors are not Always Observed
7. Optimal Rates of Aggregation (Annual Conference Computational Learning Theory)
8. Group Sequential Methods with Applications to Clinical Trials
9. Test Martingales, Bayes Factors and p-Values
10. Time-uniform, nonparametric, nonasymptotic confidence sequences

Their papers

• A Sound and Complete Algorithm for Learning Causal Models from Relational Data (2013) — 62 citations
• Time-uniform central limit theory and asymptotic confidence sequences (2021) — 52 citations