Here are those recent publications and preprints that were not listed on the front page. See here for an exhaustive publication list from 2020 onwards, and here for an exhaustive list until 2020 (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)