Optional Stopping with Bayes Factors: a categorization and extension of folklore results, with an application to invariant situations. - Allard Hendriksen; Rianne de Heide; Peter Grünwald (CoRR, 2018)

Safe-Bayesian Generalized Linear Regression. - Rianne de Heide; Alisa Kirichenko; Peter Grunwald; Nishant A. Mehta (AISTATS, 2020)

Fixed-confidence guarantees for Bayesian best-arm identification. - Xuedong Shang; Rianne de Heide; Pierre Ménard; Emilie Kaufmann; Michal Valko (AISTATS, 2020)

Safe Testing. - Peter Grünwald; Rianne de Heide; Wouter M. Koolen (ITA, 2020)

Bandits with many optimal arms. - Rianne de Heide; James Cheshire; Pierre Ménard; Alexandra Carpentier (NeurIPS, 2021)

Top Two Algorithms Revisited. - Marc Jourdan; Rémy Degenne; Dorian Baudry; Rianne de Heide; Emilie Kaufmann (NeurIPS, 2022)

On the Truth-convergence of Open-Minded Bayesianism. - Tom F. Sterkenburg; Rianne de Heide (Rev. Symb. Log., 2022)

Attribution-based Explanations that Provide Recourse Cannot be Robust. - Hidde Fokkema; Rianne de Heide; Tim van Erven (J. Mach. Learn. Res., 2023)