Benjamin Guedj

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Maxime HaddoucheInriaVerified email at inria.fr
John Shawe-TaylorUCLVerified email at cs.ucl.ac.uk
Pierre AlquierESSEC Business SchoolVerified email at essec.edu
Felix BiggsPhD in Foundational AI from University College LondonVerified email at ucl.ac.uk
Arthur GrettonGatsby Computational Neuroscience Unit and Google DeepmindVerified email at gatsby.ucl.ac.uk
Antonin SchrabDoctor in Foundational AI, UCL (AI Centre & Gatsby Unit)Verified email at ucl.ac.uk
Antoine VendevilleSciences Po ParisVerified email at sciencespo.fr
Gérard BiauProfessor, Sorbonne University, ParisVerified email at sorbonne-universite.fr
Ilmun KimYonsei UniversityVerified email at yonsei.ac.kr
Pascal GermainAssociate Professor, Université LavalVerified email at ift.ulaval.ca
Shi ZHOUDepartment of Computer Science, University College London (UCL), UKVerified email at ucl.ac.uk
Paul ViallardResearcher, LACODAM Team, INRIA Rennes, IRISAVerified email at inria.fr
Mark HarmanResearch Scientist at Meta & Professor of Software Engineering at UCLVerified email at ucl.ac.uk
Earl T. BarrProfessor, University College LondonVerified email at ucl.ac.uk
Maria Perez-OrtizAssociate Professor, University College LondonVerified email at ucl.ac.uk
Zakaria MhammediGoogle ResearchVerified email at mit.edu
Mélisande AlbertINSA de ToulouseVerified email at insa-toulouse.fr
Béatrice Laurent,INSA de Toulouse, Institut de Mathématiques de ToulouseVerified email at insa-toulouse.fr
Arnaud DoucetGoogle DeepMindVerified email at google.com
Jie M. ZhangLecturer (Assistant Professor), King's College LondonVerified email at kcl.ac.uk

Benjamin Guedj

Inria and University College London (UCL)

Verified email at inria.fr - Homepage

Machine learning Deep learning Statistical learning theory Computational statistics AI


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
A Primer on PAC-Bayesian Learning B Guedj, J Shawe-Taylor ICML 2019, 2019	266	2019
Simpler PAC-Bayesian bounds for hostile data P Alquier, B Guedj Machine Learning 107 (5), 887-902, 2018	92	2018
MMD aggregated two-sample test A Schrab, I Kim, M Albert, B Laurent, B Guedj, A Gretton Journal of Machine Learning Research 24 (194), 1-81, 2023	82	2023
PAC-Bayesian Estimation and Prediction in Sparse Additive Models B Guedj, P Alquier Electronic Journal of Statistics 7, 264-291, 2013	69	2013
COBRA: A combined regression strategy G Biau, A Fischer, B Guedj, JD Malley Journal of Multivariate Analysis 146, 18-28, 2016	64*	2016
Dichotomize and generalize: PAC-Bayesian binary activated deep neural networks G Letarte, P Germain, B Guedj, F Laviolette Advances in Neural Information Processing Systems 32, 2019	62	2019
PAC-Bayes unleashed: Generalisation bounds with unbounded losses M Haddouche, B Guedj, O Rivasplata, J Shawe-Taylor Entropy 23 (10), 1330, 2021	58	2021
PAC-Bayes un-expected Bernstein inequality Z Mhammedi, P Grünwald, B Guedj Advances in Neural Information Processing Systems 32, 2019	57	2019
Online k-means clustering V Cohen-Addad, B Guedj, V Kanade, G Rom International Conference on Artificial Intelligence and Statistics, 1126-1134, 2021	51	2021
Attributing and referencing (research) software: Best practices and outlook from Inria P Alliez, R Di Cosmo, B Guedj, A Girault, MS Hacid, A Legrand, N Rougier Computing in Science & Engineering 22 (1), 39-52, 2019	49	2019
Estimating the location and shape of hybrid zones B Guedj, G Guillot Molecular Ecology Resources 11 (6), 1119-1123, 2011	49	2011
Generalization bounds: Perspectives from information theory and PAC-Bayes F Hellström, G Durisi, B Guedj, M Raginsky Foundations and Trends® in Machine Learning 18 (1), 1-223, 2025	43	2025
Efficient Aggregated Kernel Tests using Incomplete -statistics A Schrab, I Kim, B Guedj, A Gretton Advances in Neural Information Processing Systems 35, 18793-18807, 2022	43	2022
Differentiable PAC–Bayes objectives with partially aggregated neural networks F Biggs, B Guedj Entropy 23 (10), 1280, 2021	38	2021
Model validation using mutated training labels: An exploratory study JM Zhang, M Harman, B Guedj, ET Barr, J Shawe-Taylor Neurocomputing 539, 126116, 2023	34*	2023
PAC-Bayes generalisation bounds for heavy-tailed losses through supermartingales M Haddouche, B Guedj arXiv preprint arXiv:2210.00928, 2022	33	2022
PAC-Bayesian contrastive unsupervised representation learning K Nozawa, P Germain, B Guedj Conference on Uncertainty in Artificial Intelligence, 21-30, 2020	32	2020
Stability revisited: new generalisation bounds for the leave-one-out A Celisse, B Guedj arXiv preprint arXiv:1608.06412, 2016	32	2016
Non-vacuous generalisation bounds for shallow neural networks F Biggs, B Guedj International Conference on Machine Learning, 1963-1981, 2022	31	2022
On margins and derandomisation in PAC-Bayes F Biggs, B Guedj International Conference on Artificial Intelligence and Statistics, 3709-3731, 2022	29	2022

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