activity
20032026
most citedShannon Information and Kolmogorov Complexity

136 citations · 816 across the 52 of their papers we have counts for

collaborators

56 papers

cond-mat.mes-hall2026

Interaction between Rydberg Excitons in Cuprous Oxide Revealed through Resonant Second Harmonic Generation

Andreas Farenbruch, Henje Stolz, Peter Grünwald +5

We report experimental and theoretical investigations of interacting excitons of the yellow series in cuprous oxide (CuO) with principal quantum numbers up to by means of secon…

stat.ME2026

E-values as statistical evidence: A comparison to Bayes factors, likelihoods, and p-values

Ben Chugg, Aaditya Ramdas, Peter Grünwald

A recurring debate in the philosophy of statistics concerns what, exactly, should count as a measure of evidence for or against a given hypothesis. P-values, likelihood ratios, and…

cond-mat.stat-mech2023★ 3 cited

Description length of canonical and microcanonical models

Francesca Giuffrida, Tiziano Squartini, Peter Grünwald +1

The (non-)equivalence of canonical and microcanonical ensembles is a fundamental question in statistical physics, concerning whether the use of soft and hard constraints in the max…

cs.IT2023★ 2 cited

Reverse Information Projections and Optimal E-statistics

Tyron Lardy, Peter Grünwald, Peter Harremoës

Information projections have found important applications in probability theory, statistics, and related areas. In the field of hypothesis testing in particular, the reverse inform…

math.ST2023★ 2 cited

Exponential Stochastic Inequality

Peter D. Grünwald, Muriel F. Pérez-Ortiz, Zakaria Mhammedi

We develop the concept of exponential stochastic inequality (ESI), a novel notation that simultaneously captures high-probability and in-expectation statements. It is especially we…

stat.ME2023★ 1 cited

E-values for k-Sample Tests With Exponential Families

Yunda Hao, Peter Grünwald, Tyron Lardy +2

We develop and compare e-variables for testing whether samples of data are drawn from the same distribution, the alternative being that they come from different elements of an…

stat.ME2023★ 3 cited

Safe Sequential Testing and Effect Estimation in Stratified Count Data

Rosanne J. Turner, Peter D. Grünwald

Sequential decision making significantly speeds up research and is more cost-effective compared to fixed-n methods. We present a method for sequential decision making for stratifie…

math.ST2023

The E-Posterior

Peter Grünwald

We develop a representation of a decision maker's uncertainty based on e-variables. Like the Bayesian posterior, this *e-posterior* allows for making predictions against arbitrary…

math.ST2022★ 8 cited

Game-theoretic statistics and safe anytime-valid inference

Aaditya Ramdas, Peter Grünwald, Vladimir Vovk +1

Safe anytime-valid inference (SAVI) provides measures of statistical evidence and certainty -- e-processes for testing and confidence sequences for estimation -- that remain valid…

stat.ME2022★ 1 cited

Anytime Valid Tests of Conditional Independence Under Model-X

Peter Grünwald, Alexander Henzi, Tyron Lardy

We propose a sequential, anytime-valid method to test the conditional independence of a response and a predictor given a random vector . The proposed test is based on e-…

math.ST2022★ 1 cited

E-Statistics, Group Invariance and Anytime Valid Testing

Muriel Felipe Pérez-Ortiz, Tyron Lardy, Rianne de Heide +1

We study worst-case-growth-rate-optimal (GROW) e-statistics for hypothesis testing between two group models. It is known that under a mild condition on the action of the underlying…

stat.ME2022★ 1 cited

Beyond Neyman-Pearson: e-values enable hypothesis testing with a data-driven alpha

Peter Grünwald

A standard practice in statistical hypothesis testing is to mention the p-value alongside the accept/reject decision. We show the advantages of mentioning an e-value instead. With…

stat.ME2022★ 1 cited

Exact Anytime-valid Confidence Intervals for Contingency Tables and Beyond

Rosanne Turner, Peter Grünwald

E-variables are tools for retaining type-I error guarantee with optional stopping. We extend E-variables for sequential two-sample tests to general null hypotheses and anytime-vali…

stat.ML2022★ 1 cited

Minimax risk classifiers with 0-1 loss

Santiago Mazuelas, Mauricio Romero, Peter Grünwald

Supervised classification techniques use training samples to learn a classification rule with small expected 0-1 loss (error probability). Conventional methods enable tractable lea…

stat.ME2021★ 2 cited

ALL-IN meta-analysis: breathing life into living systematic reviews and prospective meta-analyses

Judith ter Schure, Peter Grünwald

Science is justly admired as a cumulative process ("standing on the shoulders of giants"), yet scientific knowledge is typically built on a patchwork of research contributions with…

stat.ME2021★ 4 cited

Generic E-Variables for Exact Sequential k-Sample Tests that allow for Optional Stopping

Rosanne Turner, Alexander Ly, Peter Grünwald

We develop E-variables for testing whether two or more data streams come from the same source or not, and more generally, whether the difference between the sources is larger than…

cs.LG2021★ 16 cited

Robust subgroup discovery

Hugo Manuel Proença, Peter Grünwald, Thomas Bäck +1

We introduce the problem of robust subgroup discovery, i.e., finding a set of interpretable descriptions of subsets that 1) stand out with respect to one or more target attributes,…

stat.ME2020★ 1 cited

The Anytime-Valid Logrank Test: Error Control Under Continuous Monitoring with Unlimited Horizon

J. ter Schure, M. F. Perez-Ortiz, A. Ly +1

We introduce the anytime-valid (AV) logrank test, a version of the logrank test that provides type-I error guarantees under optional stopping and optional continuation. The test is…

math.ST2020★ 2 cited

Minimax rates without the fixed sample size assumption

Alisa Kirichenko, Peter Grünwald

We generalize the notion of minimax convergence rate. In contrast to the standard definition, we do not assume that the sample size is fixed in advance. Allowing for varying sample…

math.ST2019★ 18 cited

Safe-Bayesian Generalized Linear Regression

Rianne de Heide, Alisa Kirichenko, Nishant Mehta +1

We study generalized Bayesian inference under misspecification, i.e. when the model is 'wrong but useful'. Generalized Bayes equips the likelihood with a learning rate . We show…

math.ST2019★ 10 cited

Safe Testing

Peter Grünwald, Rianne de Heide, Wouter Koolen

We develop the theory of hypothesis testing based on the e-value, a notion of evidence that, unlike the p-value, allows for effortlessly combining results from several studies in t…

cs.LG2019★ 9 cited

PAC-Bayes Un-Expected Bernstein Inequality

Zakaria Mhammedi, Peter D. Grunwald, Benjamin Guedj

We present a new PAC-Bayesian generalization bound. Standard bounds contain a $\sqrt{L_n \cdot \KL/n}$ complexity term which dominates unless , the empirical error of the lear…

quant-ph2017★ 56 cited

Effective second-order correlation function and single-photon detection

Peter Grünwald

Quantum-optical research on semiconductor single-photon sources puts special emphasis on the measurement of the second-order correlation function , arguing that $g^{(2)…

cond-mat.mtrl-sci2017★ 55 cited

Rydberg excitons in the presence of an ultralow-density electron-hole plasma

J. Heckötter, M. Freitag, D. Fröhlich +7

We use two-color pump-probe spectroscopy to study Rydberg excitons in CuO in the presence of free carriers injected by above-band-gap excitation. Already at plasma densities $ρ…