Avi Feller
Statistics and Probability · 2015–2021
A researcher in the Science corpus: 9 papers; trusts 78 researchers and is trusted by 15 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 194 citations into it; #6,780 of 12,932 by trust here, #3,411 by citations
- Causal Inference & Discovery — 47 citations into it
- Economics and Econometrics — 43 citations into it
- Artificial Intelligence — 42 citations into it
- Sociology and Political Science — 28 citations into it
- Education — 22 citations into it
- Safety Research — 17 citations into it
- Statistical Learning Theory — 13 citations into it
Whom Avi Feller trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Donald B. Rubin
- Guido W. Imbens
- Joshua D. Angrist
- Alberto Abadie
- Andrew Gelman
- Susan Athey
- Paul R. Rosenbaum
- James M. Robins
- James J. Heckman
- Kosuke Imai
Who trusts Avi Feller overall
- Peng Ding
- Lihua Lei
- Stefan Wager
- Susan Athey
- Alexandra Chouldechova
- E.J. Candes
- Zachary Chase Lipton
- Luke W. Miratrix
- Lingxiao Huang
Papers from Avi Feller's perspective
Ordered by how strongly the researchers Avi Feller trusts endorse each paper. Same corpus, a different order for every researcher.
- Regression Shrinkage and Selection via the Lasso
- [On the Application of Probability Theory to Agricultural Experiments. Essay on Principles. Section 9.] Comment: Neyman (1923) and Causal Inference in Experiments and Observational Studies
- The central role of the propensity score in observational studies for causal effects
- ImageNet classification with deep convolutional neural networks
- Estimating causal effects of treatments in randomized and nonrandomized studies.
- Statistics and Causal Inference
- Observational Studies
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Estimation of Regression Coefficients When Some Regressors are not Always Observed
Their papers
- Decomposing Treatment Effect Variation (2016) — 98 citations
- Principal Stratification (2015) — 27 citations
- Overlap in observational studies with high-dimensional covariates (2017) — 229 citations
- Assessing Treatment Effect Variation in Observational Studies: Results from a Data Challenge (2019) — 47 citations
- The Augmented Synthetic Control Method (2018) — 479 citations
- Randomization tests of causal effects under interference (2019) — 100 citations
- The Balancing Act in Causal Inference (2021) — 72 citations
- Algorithmic Decision Making and the Cost of Fairness (2017) — 1,410 citations
- Compared to what? Variation in the impacts of early childhood education by alternative care type (2016) — 125 citations