Here are those recent publications and preprints that were not listed on the front page. See here for an exhaustive publication list (or check google scholar, of course…).

Preprints

• Judith ter Schure and M. Perez and A. Ly and G.. The Safe Logrank Test: Error Control under Continuous Monitoring with Unlimited Horizon. https://arxiv.org/abs/2011.069311, 2021.
• Rosanne Turner, A. Ly and G. Generic E-Variables for Exact Sequential k-Sample Tests that allow for Optional Stopping,  https://arxiv.org/abs/2106.02693, 2021.
• Santiago Mazuelas, Mauricio Romero, G. Minimax risk classifiers with 0-1 loss, https://arxiv.org/abs/2201.06487, 2022.

Other Recent Publications on E-Values and “Safe Testing”

• Rosanne Turner and G. Exact Anytime-valid Confidence Intervals for Contingency Tables and Beyond, accepted for publication in Statistics and Probability letters, 2023. Also at   https://arxiv.org/abs/2203.09785.
• Wouter Koolen and G. Log-Optimal Anytime-Valid E-Values. International Journal of Approximate Reasoning, 2021.
• Judith ter Schure and G., 2019.   Accumulation Bias in meta-analysis: the need to consider time in error control. F1000Research 2019, 8:962 (https://doi.org/10.12688/f1000research.19375.1)

Recent Publications on Quite Different Other Stuff

• Tom Sterkenburg and P. Grünwald. The No-Free Lunch Theorems of Supervised Learning. Synthese, 2021.
• P.D. Grünwald and T. Roos. Minimum Description Length Revisited. International Journal of Mathematics for Industry, Nov. 2019.
• P.D. Grünwald. Safe Probability.  Journal of Statistical Planning and Inference 195, 2018, pp. 47-63.

Recent Publications on PAC-Bayes, Excess Risk Bounds, “Safe” and Generalized Bayesian Inference

• 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.
• Rianne de Heide and Alisa Kirichenko and Nishant Mehta and Peter Grünwald. Safe Bayesian Generalized Linear Regression. AIStats, 2020.
• P.D. Grünwald and N. Mehta.  Fast Rates for General Unbounded Loss Functions: from ERM to Generalized Bayes. Journal of Machine Learning Research, 2020
• P.D. Grünwald and N. Mehta, Proceedings ALT (Algorithmic Learning Theory) 2019. A Tight Excess Risk Bound via a Unified PAC-Bayesian-Rademacher-Shtarkov-MDL Complexity.
• Z. Mhammedi and P.D. Grünwald and B. Guedj, 2019. PAC-Bayes Unexpected Bernstein Inequality. Proceedings of NeurIPS 2019.
• P.D. Grünwald and T. van Ommen. Inconsistency of Bayesian Inference for Misspecified Linear Models, and a Proposal for Repairing It . Bayesian Analysis, 2017, pp. 1069-1103. Here is a video recording of a talk I gave about the subject at the NIPS 2014 workshop From Bad Models to Good Policies. And here is a small erratum (one formula was wrong in Section 2.5)