All publications and research outputs

This is a single reverse-chronological view of the material listed on the Research page, irrespective of topic.

2026

• Carefree multiple testing with e-processes
  Yury Tavyrikov, Jelle J. Goeman and Rianne de Heide
  Electronic Journal of Statistics 20 (2026), no. 2. doi:10.1214/26-EJS2546    arxiv proc

• Dynamic e-closure for online hypotheses with any-time-valid evidence: closure principles and projective mergers
  Rianne de Heide
  arxiv, 2026

• Anytime-valid log-rank testing for randomised trials
  Joren Brunekreef, Renee Menezes and Rianne de Heide
  Poster presented at SAVI, July 2 2026, paper in preparation.    poster

• E-values for early decisions in clinical trials
  Rianne de Heide, partly based on joint work with Nynke Luijten and Vincent van der Noort
  Poster presented at SAVI, July 2 2026, both papers in preparation.    poster

• Multiple testing with any-time valid evidence
  Yury Tavyrikov, Jelle Goeman and Rianne de Heide
  Poster presented at SAVI, June 30 2026, paper in preparation.    poster

• Permutation-based FDR control via the e-closure principle
  Rovanos Tsafack Nzanguim, Aurele Mingam, Jelle Goeman and Rianne de Heide
  Poster presented at SAVI, June 30 2026, paper in preparation.    poster

• Bringing Flexibility to the Benjamini-Hochberg Procedure
  Aurele Mingam, Rovanos Tsafack Nzanguim, Rianne de Heide and Jelle Goeman
  Poster presented at SAVI, June 30 2026, paper in preparation.    poster

• Interactive Edge Orientation Identification: An Optimization Approach
  Fabian Damken, Wouter Koolen and Rianne de Heide
  Poster presented at SAVI, June 29 2026, paper in preparation.    poster

2025

• Bringing Closure to False Discovery Rate Control: A General Principle for Multiple Testing
  Ziyu Xu, Aldo Solari, Lasse Fischer, Rianne de Heide, Aaditya Ramdas, and Jelle Goeman
  arXiv, 2025    software: R (eClosure) Python (eclosure)
  This work subsumes: The e-Partitioning Principle of False Discovery Rate Control
  Jelle Goeman, Rianne de Heide and Aldo Solari
  Arxiv, 2025, submitted

• Authorship verification of the Deutero-Pauline letters through deep learning
  Evy Beijen and Rianne de Heide
  HIPHIL Novum, 10(1), 22–39, 2025. https://doi.org/10.7146/hn.v10i1.147482    proc
  

2024

• Safe Testing
  Peter Grünwald, Rianne de Heide and Wouter Koolen
  Journal of the Royal Statistical Society Series B: Statistical Methodology, Volume 86, Issue 5, November 2024, Pages 1091–1128. doi.org/10.1093/jrsssb/qkae011    arxiv proc
  The discussion meeting took place on January 24, 2024 (video).
  
  Authors’ Reply to the Discussion of ‘Safe Testing’
  Peter Grünwald, Rianne de Heide and Wouter Koolen
  Journal of the Royal Statistical Society Series B: Statistical Methodology, Volume 86, Issue 5, November 2024, Pages 1163–1171. doi:10.1093/jrsssb/qkae069    proc

• E-statistics, group invariance and any time valid testing
  Muriel Felipe Pérez-Ortiz, Tyron Lardy, Rianne de Heide and Peter Grünwald
  The Annals of Statistics, 52(4), pp.1410-32    PDF arxiv proc
  

2023

• Interpreting Generalized Bayesian Inference by Generalized Bayesian Inference
  Julian Rodemann, Thomas Augustin and Rianne de Heide
  ISIPTA 2023    poster

• Attribution-based Explanations that Provide Recourse Cannot be Robust
  Hidde Fokkema, Rianne de Heide and Tim van Erven
  Journal of Machine Learning Research, 24(360), pp.1-37, 2023.   arxiv proc

2022

• Top Two Algorithms Revisited
  Marc Jourdan, Rémy Degenne, Dorian Baudry, Rianne de Heide and Emilie Kaufmann
  Advances in Neural Information Processing Systems 35 (2022): 26791-26803    arxiv proc poster

• The truth-convergence of open-minded Bayesianism
  Tom F. Sterkenburg and Rianne de Heide
  The Review of Symbolic Logic 15(1):64-100, 2022, doi:10.1017/S1755020321000022    philsci archive   proc
  Accepted to the Formal Epistemology Workshop 2019, and the biennial conference of the European Philosophy of Science Association.

2021

• Bandits with many optimal arms
  Rianne de Heide, James Cheshire, Pierre Ménard and Alexandra Carpentier
  Advances in Neural Information Processing Systems 34 (2021): 22457-22469    arxiv proc poster

• Optional Stopping with Bayes Factors: A Categorization and Extension of Folklore Results, with an Application to Invariant Situations
  Allard Hendriksen, Rianne de Heide and Peter Grünwald
  Bayesian Analysis 16(3):961–989, 2021, doi:10.1214/20-BA1234.    arxiv   proc

• Why optional stopping can be a problem for Bayesians
  Rianne de Heide and Peter Grünwald
  Psychonomic Bulletin & Review 28(3):795-812, 2021, doi:10.3758/s13423-020-01803-x    proc
  Extended technical report: arxiv 1708.08278

• God, the beautiful and mathematics: a response
  Peter-Ben Smit and Rianne de Heide
  HTS Teologiese Studies / Theological Studies 2021, Vol 77, No 4, doi.org/10.4102/hts.v77i4.6208    proc

2020

• Bayesian Learning: Challenges, Limitations and Pragmatics (PhD Dissertation)
  Rianne de Heide, 2020    url

• Safe-Bayesian Generalized Linear Regression
  Rianne de Heide, Alisa Kirichenko, Nishant Mehta and Peter Grünwald
  AISTATS 2020, PMLR 108:2623-2633.    arxiv   proc   code   talk

• Fixed-Confidence Guarantees for Bayesian Best-Arm Identification
  Xuedong Shang, Rianne de Heide, Emilie Kaufmann, Pierre Ménard and Michal Valko
  AISTATS 2020, PMLR 108:1823-1832.    arxiv   proc   talk

2018

• Invited discussion to the paper Using Stacking to Average Bayesian Predictive Distributions by Yao, Vehtari, Simpson and Gelman
  Peter Grünwald and Rianne de Heide
  Bayesian Analysis 13 (2018), no. 3, 917-1003.    proc
  

2016

• The Safe-Bayesian Lasso (MSc Thesis)
  Rianne de Heide, 2016    url poster

Software

• R package SafeBayes
  Rianne de Heide, 2016