Andrew Gelman - RankMe

51 papers A* 3B 1C 1Journal 43Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Conformal Prediction and Human Decision Making. CoRR Jessica Hullman, Yifan Wu, Dawei Xie, Ziyang Guo, Andrew Gelman
2025	J	`jnl`	Power Analysis is Essential: High-Powered Tests Suggest Minimal to No Effect of Rounded Shapes on Click-Through Rates. CoRR Ron Kohavi, Jakub Linowski, Lukas Vermeer, Fabrice Boisseranc, Joachim Furuseth, Andrew Gelman, Guido Imbens, Ravikiran Rajagopal
2025	J	`jnl`	Visualizing distributions of covariance matrices. J. Data Sci. Stat. Vis. Tomoki Tokuda, Ben Goodrich, Iven Van Mechelen, Andrew Gelman, Francis Tuerlinckx
2024	J	`jnl`	Bayesian workflow for time-varying transmission in stratified compartmental infectious disease transmission models. PLoS Comput. Biol. Judith A. Bouman, Anthony Hauser, Simon L. Grimm, Martin Wohlfender, Samir Bhatt, Elizaveta Semenova, Andrew Gelman, Christian L. Althaus, Julien Riou
2024	J	`jnl`	Pareto Smoothed Importance Sampling. J. Mach. Learn. Res. Aki Vehtari, Daniel Simpson, Andrew Gelman, Yuling Yao, Jonah Gabry
2024	J	`jnl`	Statistics as a Social Activity: Attitudes toward Amalgamating Evidence. Entropy Andrew Gelman, Keith O'Rourke
2023	J	`jnl`	Artificial Intelligence and Aesthetic Judgment. CoRR Jessica Hullman, Ari Holtzman, Andrew Gelman
2023	J	`jnl`	Bayesian spatial modelling of localised SARS-CoV-2 transmission through mobility networks across England. PLoS Comput. Biol. Thomas Ward, Mitzi Morris, Andrew Gelman, Bob Carpenter, William Ferguson, Christopher E. Overton, Martyn Fyles
2023	A*	`conf`	Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach. ICLR Han Guo, Philip Greengard, Hongyi Wang, Andrew Gelman, Yoon Kim, Eric P. Xing
2023	J	`jnl`	Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach. CoRR Han Guo, Philip Greengard, Hongyi Wang, Andrew Gelman, Yoon Kim, Eric P. Xing
2023	J	`jnl`	Prediction scoring of data-driven discoveries for reproducible research. Stat. Comput. Anna L. Smith, Tian Zheng, Andrew Gelman
2022	J	`jnl`	A fast regression via SVD and marginalization. Comput. Stat. Philip Greengard, Andrew Gelman, Aki Vehtari
2022	J	`jnl`	Delivering data differently. CoRR Gwynn Sturdevant, A. Jonathan R. Godfrey, Andrew Gelman
2022	J	`jnl`	Pathfinder: Parallel quasi-Newton variational inference. J. Mach. Learn. Res. Lu Zhang, Bob Carpenter, Andrew Gelman, Aki Vehtari
2022	J	`jnl`	Selecting on statistical significance and practical importance is wrong. J. Inf. Technol. Blakeley B. McShane, Andrew Gelman
2022	J	`jnl`	Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal Posteriors. J. Mach. Learn. Res. Yuling Yao, Aki Vehtari, Andrew Gelman
2022	C	`conf`	The Worst of Both Worlds: A Comparative Analysis of Errors in Learning from Data in Psychology and Machine Learning. AIES Jessica Hullman, Sayash Kapoor, Priyanka Nanayakkara, Andrew Gelman, Arvind Narayanan
2022	J	`jnl`	The worst of both worlds: A comparative analysis of errors in learning from data in psychology and machine learning. CoRR Jessica Hullman, Sayash Kapoor, Priyanka Nanayakkara, Andrew Gelman, Arvind Narayanan
2021	J	`jnl`	Accounting for uncertainty during a pandemic. Patterns Jon Zelner, Julien Riou, Ruth Etzioni, Andrew Gelman
2021	J	`jnl`	Bayesian hierarchical stacking. CoRR Yuling Yao, Gregor Pirs, Aki Vehtari, Andrew Gelman
2021	J	`jnl`	Pathfinder: Parallel quasi-Newton variational inference. CoRR Lu Zhang, Bob Carpenter, Andrew Gelman, Aki Vehtari
2021	J	`jnl`	Reviews. Am. Math. Mon. Darren B. Glass, Béla Bajnok, Carolyn Yackel, Edray Goins, Jenna P. Carpenter, Stephen Kennedy, Jeanette Shakalli, Ursula Whitcher, Dave Kung, Kathryn Kozak, Robert Ghrist, Andrew Gelman
2021	J	`jnl`	To design interfaces for exploratory data analysis, we need theories of graphical inference. CoRR Jessica Hullman, Andrew Gelman
2021	J	`jnl`	Toward a Taxonomy of Trust for Probabilistic Machine Learning. CoRR Tamara Broderick, Andrew Gelman, Rachael Meager, Anna L. Smith, Tian Zheng
2020	J	`jnl`	A Fast Linear Regression via SVD and Marginalization. CoRR Philip Greengard, Andrew Gelman, Aki Vehtari
2020	J	`jnl`	Expectation Propagation as a Way of Life: A Framework for Bayesian Inference on Partitioned Data. J. Mach. Learn. Res. Aki Vehtari, Andrew Gelman, Tuomas Sivula, Pasi Jylänki, Dustin Tran, Swupnil Sahai, Paul Blomstedt, John P. Cunningham, David Schiminovich, Christian P. Robert
2018	A*	`conf`	Yes, but Did It Work?: Evaluating Variational Inference. ICML Yuling Yao, Aki Vehtari, Daniel Simpson, Andrew Gelman
2017	—	`conf`	A Safe Depth Forecasting Model for Insuring Tubewell Installations Against Arsenic Risk in Bangladesh. ICCSA (5) Matilde Trevisani, Jie Shen, Alexander van Geen, Andrew Gelman, Shuky Ehrenberg, John Immel
2017	J	`jnl`	Automatic Differentiation Variational Inference. J. Mach. Learn. Res. Alp Kucukelbir, Dustin Tran, Rajesh Ranganath, Andrew Gelman, David M. Blei
2017	J	`jnl`	Erratum to: Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Stat. Comput. Aki Vehtari, Andrew Gelman, Jonah Gabry
2017	J	`jnl`	Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Stat. Comput. Aki Vehtari, Andrew Gelman, Jonah Gabry
2017	J	`jnl`	The Prior Can Often Only Be Understood in the Context of the Likelihood. Entropy Andrew Gelman, Daniel Simpson, Michael Betancourt
2017	B	`conf`	The statistical significance filter leads to overconfident expectations of replicability. CogSci Shravan Vasishth, Andrew Gelman
2016	J	`jnl`	Automatic Differentiation Variational Inference. CoRR Alp Kucukelbir, Dustin Tran, Rajesh Ranganath, Andrew Gelman, David M. Blei
2016	—	`ch.`	Centralized Analysis of Local Data, with Dollars and Lives on the Line: Lessons from the Home Radon Experience. Computational Social Science Phillip N. Price, Andrew Gelman
2015	—	`conf`	Automatic Variational Inference in Stan. NIPS Alp Kucukelbir, Rajesh Ranganath, Andrew Gelman, David M. Blei
2015	J	`jnl`	Simulation-efficient shortest probability intervals. Stat. Comput. Ying Liu, Andrew Gelman, Tian Zheng
2014	J	`jnl`	The Mythical Swing Voter. CoRR David Rothschild, Sharad Goel, Andrew Gelman, Doug Rivers
2014	J	`jnl`	The No-U-turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo. J. Mach. Learn. Res. Matthew D. Hoffman, Andrew Gelman
2014	J	`jnl`	Understanding predictive information criteria for Bayesian models. Stat. Comput. Andrew Gelman, Jessica Hwang, Aki Vehtari
2012	J	`jnl`	In praise of the referee CoRR Nicolas Chopin, Andrew Gelman, Kerrie L. Mengersen, Christian P. Robert
2011	J	`jnl`	The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo CoRR Matthew D. Hoffman, Andrew Gelman
2009	J	`jnl`	Commentary - Discussion of the Article "Website Morphing". Mark. Sci. Andrew Gelman
2007	J	`jnl`	Manipulating and summarizing posterior simulations using random variable objects. Stat. Comput. Jouni Kerman, Andrew Gelman
2007	J	`jnl`	Weighted Classical Variogram Estimation for Data With Clustering. Technometrics Cavan Reilly, Andrew Gelman
2006	J	`jnl`	An experimental study of storable votes. Games Econ. Behav. Alessandra Casella, Andrew Gelman, Thomas R. Palfrey
2006	J	`jnl`	Bayesian Measures of Explained Variance and Pooling in Multilevel (Hierarchical) Models. Technometrics Andrew Gelman, Iain Pardoe
2006	J	`jnl`	Multilevel (Hierarchical) Modeling: What It Can and Cannot Do. Technometrics Andrew Gelman
2000	J	`jnl`	Bayesian probabilistic extensions of a deterministic classification model. Comput. Stat. Iwin Leenen, Iven Van Mechelen, Andrew Gelman
2000	J	`jnl`	Type S error rates for classical and Bayesian single and multiple comparison procedures. Comput. Stat. Andrew Gelman, Francis Tuerlinckx
1988	A*	`conf`	FRM: An Intelligent Assistant for Financial Resource Management. AAAI Andrew Gelman, Susan Altman, Matt Pallakoff, Ketan Doshi, Catherine Manago, Thomas C. Rindfleisch, Bruce G. Buchanan