General theory for Big Bayes

Project Information

GTBB

Grant agreement ID: 834175

DOI 10.3030/834175

EC signature date 10 May 2019

Start date 1 October 2019

End date 31 March 2025

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost € 2 176 702,00

EU contribution € 2 176 702,00

Coordinated by

UNIVERSITE PARIS DAUPHINE
France

Publications

Other (13)

Ideal Bayesian Spatial Adaptation

Author(s): Veronicka Rockova; Judith Rousseau
Published in: 2021
Publisher: arxiv
DOI: 10.48550/arxiv.2105.12793

Mean-field Behaviour of Neural Tangent Kernel for Deep Neural Networks

Author(s): Soufiane Hayou, Arnaud Doucet, Judith Rousseau
Published in: 2020
Publisher: arxiv
DOI: 10.48550/arxiv.1905.13654

Minimax rates without the fixed sample size assumption

Author(s): Alisa Kirichenko, Peter Grünwald
Published in: 2020
Publisher: Arxiv

Efficient Bayesian estimation and use of cut posterior in semiparametric hidden Markov models

Author(s): Daniel Moss Judith Rousseau
Published in: 2022
Publisher: Arxiv

Evidence estimation in finite and infinite mixture models and applications

Author(s): Adrien Hairault; Christian P. Robert, Judith Rousseau
Published in: 2022
Publisher: arxiv
DOI: 10.48550/arxiv.2205.05416

Imposing Gaussian Pre-Activations in a Neural Network

Author(s): Pierre Wolinsky, Julyan Arbel
Published in: 2022
Publisher: arxiv
DOI: 10.48550/arxiv.2205.12379

An Equivalence between Bayesian Priors and Penalties in Variational Inference

Author(s): Pierre Wolinski, Guillaume Charpiat, Yann Ollivier
Published in: 2021
Publisher: Arxiv

Asymptotic Analysis of Statistical Estimators related to MultiGraphex Processes under Misspecification

Author(s): Zacharie Naulet: Judith Rousseau; François Caron
Published in: 2021
Publisher: arxiv
DOI: 10.48550/arxiv.2107.01120

On sparsity, power-law and clustering properties of graphex processes

Author(s): F. Caron, F. Panero and J. Rousseau
Published in: 2020
Publisher: Arxiv

Wasserstein convergence in Bayesian deconvolution models

Author(s): Judith Rousseau Catia Scricciolo
Published in: 2022
Publisher: arxiv

Besov priors in density estimation: optimal posterior contraction rates and adaptation

Author(s): Matteo Giordano
Published in: 2022
Publisher: Arxiv
DOI: 10.48550/arxiv.2208.14350

Bayesian estimation of nonlinearHawkes process

Author(s): D. Sulem, V. Rivoirard and J. Rousseau
Published in: 2021
Publisher: Arxiv

Fast Bayesian Coresets via Subsampling and Quasi-Newton Refinement

Author(s): Cian Naik Trevor Campbell Judith Rousseau
Published in: 2022
Publisher: Arxiv

Conference proceedings (5)

Safe-Bayesian Generalized Linear Regression

Author(s): Rianne de Heide, Alisa Kirichenko, Nishant Mehta, Peter Grünwald
Published in: AISTATs, 2020
Publisher: MLR

Bayesian nonparametrics for sparse dynamic networks

Author(s): Cian Naik, Francois Caron, Judith Rousseau, Yee Whye Teh, Konstantina Palla
Published in: European Conference on Machine Learning and Data Mining, 2022
Publisher: ECML PKDD
DOI: 10.48550/arxiv.1607.01624

On the inability of Gaussian process regression to optimally learn compositional functions

Author(s): Matteo Giordano, Johannes Schmidt-Hieber, Kolyan Ra
Published in: Advances in Neural Information Processing Systems 36, Issue 10495258, 2022, ISSN 1049-5258
Publisher: NeurIPS
DOI: 10.48550/arxiv.2205.07764

The Curse of Depth in Kernel Regime

Author(s): Soufiane Hayou;Arnaud Doucet; Judith Rousseau
Published in: 2021
Publisher: PMLR

Stable Resnet

Author(s): Hayou, Soufiane and Clerico, Eugenio and He, Bobby and Deligiannidis, George and Doucet, Arnaud and Rousseau, Judith
Published in: Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, Issue 130, 2021, Page(s) 1324--1332
Publisher: PMLR

Peer reviewed articles (2)

Sparse networks with core-periphery structure

Author(s): Cian Naik, Caron François, Judith Rousseau
Published in: Electronic Journal of Statistics, Issue 15, 2021, Page(s) 1814-1868, ISSN 1935-7524
Publisher: Institute of Mathematical Statistics
DOI: 10.1214/21-ejs1819

Simple discrete-time self-exciting models can describe complex dynamic processes: A case study of COVID-19

Author(s): Raiha Browning, Deborah Sulem, Kerrie Mengersen, Vincent Rivoirard, Judith Rousseau
Published in: PLOS ONE, Issue 16/4, 2021, Page(s) e0250015, ISSN 1932-6203
Publisher: Public Library of Science
DOI: 10.1371/journal.pone.0250015

Non-peer reviewed articles (1)

Nonparametric Bayesian Inference for Reversible Multi-Dimensional Diffusions

Author(s): Matteo Giordano; Kolyan Ray
Published in: The Annals of Statistics, Issue 00905364, 2022, ISSN 0090-5364
Publisher: Institute of Mathematical Statistics
DOI: 10.48550/arxiv.2012.12083