Here is a full list of publications and preprints since 2020 (last updated July 2023). See here for an exhaustive publication list until 2020.

Preprints

• The Safe Logrank Test: Error Control under Continuous Monitoring with Unlimited Horizon (with J. ter Schure, M. Pérez and A. Ly), 2021. arXiv
• Generic E-Variables for Exact Sequential k-Sample Tests that allow for Optional Stopping (with Rosanne Turner and Alexander Ly), 2021. arXiv
• E-Statistics, Group Invariance and Anytime Valid Testing (with Muriel Felipe Pérez-Ortiz, Tyron Lardy, Rianne de Heide), 2022. arXiv
• Beyond Neyman-Pearson, 2022. arXiv
• E-values for k-Sample Tests With Exponential Families (with Yunda Hao, Tyron Lardy, Long Long, Reuben Adams), arXiv
• Bacillus Calmette-Guérin vaccine to reduce COVID-19 infections and hospitalisations in healthcare workers – a living systematic review and prospective ALL-IN meta-analysis of individual participant data from randomised controlled trials (with J. ter Schure, A. Ly, H. van Werkhoven and  many others), 2022. medrxiv

2023

• Safe Testing (with Rianne de Heide and Wouter Koolen).  Journal of the Royal Statistical Society Series B, 2024 (to appear). arXiv
• The E-Posterior. Philosophical Transactions of the Royal Society of London Series A, 2023.  arXiv
• Game-theoretic statistics and safe anytime-valid inference (SAVI) (with A. Ramdas, V. Vovk and G. Shafer). Statistical Science, 2023 (to appear). arXiv.
• Anytime Valid Tests of Conditional Independence Under Model-X (with Alexander Henzi and Tyron Lardy). Journal of the American Statistical Association, 2023 (to appear). arXiv.
• Safe Sequential Testing and Effect Estimation in Stratified Count Data (with Rosanne Turner),  AISTATS  2023, Valencia, Spain (among 2.5% of submissions selected for oral presentation). arXiv
• Outcome prediction of electroconvulsive therapy for depression (with Yuri van der Does, Rosanne J. Turner, Miel J.H. Bartels, Karin Hagoort, Aäron Metselaar, Floortje Scheepers, Metten Somers, Edwin van Dellen). Psychiatry Research 326(6), 2023.
• Minimax risk classifiers with 0-1 loss (with Santiago Mazuelas, Mauricio Romero),  Journal of Machine Learning, 2023 (to appear). arXiv
• Exact Anytime-valid Confidence Intervals for Contingency Tables and Beyond (with Rosanne Turner). Statistics and Probability letters, 2023 (to appear). arXiv

2022

• ALL-IN meta-analysis: Breathing life into living systematic reviews (with Judith ter Schure). F1000Research, Volume 11 p. 549.1- 549.24
• Information extraction from free text for aiding transdiagnostic psychiatry: constructing NLP pipelines tailored to clinicians’ needs (with Rosanne J. Turner, Femke Coenen, Femke Roelofs, Karin Hagoort, Aki Härmä, Fleur P. Velders & Floortje E. Scheepers), BMC Psychiatry 22(1), 2022.
• Robust Subgroup Discovery (with H.M. Proenca, T. Bäck and M. van Leeuwen). Data Mining and Knowledge Discovery, 2022.

2021

• Wouter Koolen and Peter Grünwald. Log-Optimal Anytime-Valid E-Values. International Journal of Approximate Reasoning, 2021 (Festschrift for G. Shafer’s 75th birthday)
• Peter Grünwald, Thomas Steinke, Lydia Zakynthinou. PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate bounds that handle general VC classes. Proceedings COLT (Conference on Learning Theory), 2021
• Tom Sterkenburg and Peter Grünwald. The no-free-lunch theorems of supervised learning. Synthese, 2021.
• Rianne de Heide and Peter Grünwald. Why Optional Stopping Can be a Problem for Bayesians. Psychonomic Bulletin and Review 28, pp. 795-812, 2021 (see here for a slightly extended arXiv version of the paper)
• Peter D. Grünwald. Discussion of Testing by betting: A strategy for statistical and scientific communication by Glenn Shafer. Journal of the Royal Statistical Society, Series A, May 2021.

2020

• Rianne de Heide and Alisa Kirichenko and Nishant Mehta and Peter Grünwald. Safe Bayesian Generalized Linear Regression. AIStats, 2020. Also arXiv as https://arxiv.org/abs/1910.09227.
• Allard Hendriksen and Rianne de Heide and Peter Grünwald. Optional Stopping with Bayes Factors: A Categorization and Extension of Folklore Results, with an Application to Invariant Situations. Bayesian Analysis , 2020.
• P.D. Grünwald and N. Mehta.  Fast Rates for General Unbounded Loss Functions: from ERM to Generalized Bayes. Journal of Machine Learning Research, 21(56),  2020.
• H. Manuel Proenca, M. van Leeuwen, T. Bäck and P.D. Grünwald. Discovering outstanding subgroup lists for numeric targets using MDL . ECML-PKDD 2020