Rianne de Heide 个人学术档案

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	总计	2019 年至今
引用	464	452
h 指数	10	9
i10 指数	10	9

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Peter GrünwaldGroup Leader Machine Learning, CWI; Professor of Statistics, Leiden University在 cwi.nl 的电子邮件经过验证
Emilie KaufmannCNRS & Univ. Lille (CRIStAL)在 inria.fr 的电子邮件经过验证
Pierre MénardOvGU Magdeburg在 inria.fr 的电子邮件经过验证
Wouter M. KoolenCentrum Wiskunde & Informatica; University of Twente在 cwi.nl 的电子邮件经过验证
Michal ValkoLlama @ Meta Paris & Inria & MVA - Ex: Gemini and BYOL @ Google DeepMind在 meta.com 的电子邮件经过验证
Xuedong ShangINRIA (SequeL -> SCOOL)在 inria.fr 的电子邮件经过验证
Allard HendriksenPhD at CWI, Amsterdam在 cwi.nl 的电子邮件经过验证
Marc JourdanINRIA在 inria.fr 的电子邮件经过验证
Rémy DegenneInria Lille在 inria.fr 的电子邮件经过验证
Dorian BaudryENSAE, IP Paris在 ensae.fr 的电子邮件经过验证
Nishant A. MehtaAssistant Professor, University of Victoria在 uvic.ca 的电子邮件经过验证
Alisa KirichenkoUniversity of Warwick在 warwick.ac.uk 的电子邮件经过验证
James CheshireTelecom Paris在 telecom-paris.fr 的电子邮件经过验证
Hidde FokkemaPhD student, University of Amsterdam在 uva.nl 的电子邮件经过验证
Tim van ErvenAssociate professor at the University of Amsterdam, the Netherlands在 uva.nl 的电子邮件经过验证
Peter-Ben SmitVrije Universiteit Amsterdam在 vu.nl 的电子邮件经过验证
Tom F. SterkenburgMunich Center for Mathematical Philosophy在 lmu.de 的电子邮件经过验证
Thomas AugustinProfessor, Department of Statistics, University of Munich (LMU)在 stat.uni-muenchen.de 的电子邮件经过验证
Julian RodemannDepartment of Statistics, LMU Munich在 stat.uni-muenchen.de 的电子邮件经过验证
Alexandra CarpentierUni Potsdam

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Rianne de Heide

Assistant professor, Mathematics department, Vrije Universiteit Amsterdam

在 vu.nl 的电子邮件经过验证 - 首页

Machine Learning Statistics Hypothesis Testing Sequential Learning Bandits


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Safe testing P Grünwald, R de Heide, W Koolen arXiv preprint arXiv:1906.07801, 2019	175	2019
Fixed-confidence guarantees for Bayesian best-arm identification X Shang, R Heide, P Menard, E Kaufmann, M Valko International Conference on Artificial Intelligence and Statistics, 1823-1832, 2020	65	2020
Why optional stopping can be a problem for Bayesians R de Heide, PD Grünwald Psychonomic Bulletin & Review 28 (3), 795-812, 2021	56	2021
Optional stopping with Bayes factors: a categorization and extension of folklore results, with an application to invariant situations A Hendriksen, R de Heide, P Grünwald Bayesian Analysis 1 (1), 1-29, 2021	40	2021
Top two algorithms revisited M Jourdan, R Degenne, D Baudry, R de Heide, E Kaufmann Advances in Neural Information Processing Systems 35, 26791-26803, 2022	35	2022
Safe-Bayesian generalized linear regression R Heide, A Kirichenko, P Grunwald, N Mehta International Conference on Artificial Intelligence and Statistics, 2623-2633, 2020	29	2020
Bandits with many optimal arms R de Heide, J Cheshire, P Ménard, A Carpentier Advances in Neural Information Processing Systems 34, 22457-22469, 2021	19	2021
E-Statistics, Group Invariance and Anytime Valid Testing MF Pérez-Ortiz, T Lardy, R de Heide, P Grünwald arXiv preprint arXiv:2208.07610, 2022	16	2022
Attribution-based Explanations that Provide Recourse Cannot be Robust H Fokkema, R de Heide, T van Erven Journal of Machine Learning Research 24 (360), 1-37, 2023	13	2023
The Safe–Bayesian Lasso R de Heide Master's thesis, Leiden University, 2016	10	2016
On the truth-convergence of open-minded Bayesianism TF Sterkenburg, R De Heide The Review of Symbolic Logic 15 (1), 64-100, 2022	2	2022
God, the beautiful and mathematics: A response PB Smit, R Heide HTS Theological Studies 77 (4), 1-4, 2021	2	2021
Bayesian learning: Challenges, limitations and pragmatics R de Heide Leiden University, 2021	1	2021
R-Package SafeBayes R De Heide, G de los Campos, PP Rodriguez, B Wheeler, MR de Heide Freely available at CRAN Repository 1072, 1099, 2016	1	2016
Interpreting Generalized Bayesian Inference by Generalized Bayesian Inference J Rodemann, T Augustin, R de Heide Interpreting 6, 22, 2023		2023
Invited discussion to the paper" Using Stacking to Average Bayesian Predictive Distributions (with Discussion)" by Yao, Vehtari, Simpson and Gelman PD Grünwald, R de Heide Bayesian Analysis 13 (3), 957-961, 2018		2018
Invited Discussion P Grünwald, R de Heide
Optional stopping with Bayes factors: possibilities and limitations R de Heide
Generalized Bayesian Lasso R de Heide
GBRidge: Generalized Bayesian Ridge Regression R de Heide

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