Rousseau, Judith

8 publications

JMLR 2025 Nonparametric Regression on Random Geometric Graphs Sampled from Submanifolds Paul Rosa, Judith Rousseau

JMLR 2025 Scalable and Adaptive Variational Bayes Methods for Hawkes Processes Deborah Sulem, Vincent Rivoirard, Judith Rousseau

NeurIPS 2023 Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds Paul Rosa, Slava Borovitskiy, Alexander Terenin, Judith Rousseau

ECML-PKDD 2022 Bayesian Nonparametrics for Sparse Dynamic Networks Cian Naik, François Caron, Judith Rousseau, Yee Whye Teh, Konstantina Palla

NeurIPS 2022 Fast Bayesian Coresets via Subsampling and Quasi-Newton Refinement Cian Naik, Judith Rousseau, Trevor Campbell

AISTATS 2021 Stable ResNet Soufiane Hayou, Eugenio Clerico, Bobby He, George Deligiannidis, Arnaud Doucet, Judith Rousseau

NeurIPSW 2021 The Curse of Depth in Kernel Regime Soufiane Hayou, Arnaud Doucet, Judith Rousseau

ICML 2019 On the Impact of the Activation Function on Deep Neural Networks Training Soufiane Hayou, Arnaud Doucet, Judith Rousseau