Judith Rousseau

20 papers A* 3A 1Journal 14Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A principled framework for uncertainty decomposition in TabPFN. CoRR Sandra Fortini, Kenyon Ng, Sonia Petrone, Judith Rousseau, Susan Wei
2026	J	`jnl`	Persuasive Privacy. CoRR Joshua J. Bon, James Bailie, Judith Rousseau, Christian P. Robert
2025	J	`jnl`	Adaptive Diffusion Guidance via Stochastic Optimal Control. CoRR Iskander Azangulov, Peter Potaptchik, Qinyu Li, Eddie Aamari, George Deligiannidis, Judith Rousseau
2025	J	`jnl`	Nonparametric Regression on Random Geometric Graphs Sampled from Submanifolds. J. Mach. Learn. Res. Paul Rosa, Judith Rousseau
2025	J	`jnl`	Scalable and Adaptive Variational Bayes Methods for Hawkes Processes. J. Mach. Learn. Res. Déborah Sulem, Vincent Rivoirard, Judith Rousseau
2024	J	`jnl`	Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions. CoRR Iskander Azangulov, George Deligiannidis, Judith Rousseau
2023	A*	`conf`	Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds. NeurIPS Paul Rosa, Slava Borovitskiy, Alexander Terenin, Judith Rousseau
2023	J	`jnl`	Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds. CoRR Paul Rosa, Viacheslav Borovitskiy, Alexander Terenin, Judith Rousseau
2022	—	`conf`	Bayesian Nonparametrics for Sparse Dynamic Networks. ECML/PKDD (5) Cian Naik, François Caron, Judith Rousseau, Yee Whye Teh, Konstantina Palla
2022	A*	`conf`	Fast Bayesian Coresets via Subsampling and Quasi-Newton Refinement. NeurIPS Cian Naik, Judith Rousseau, Trevor Campbell
2022	J	`jnl`	Fast Bayesian Coresets via Subsampling and Quasi-Newton Refinement. CoRR Cian Naik, Judith Rousseau, Trevor Campbell
2021	A	`conf`	Stable ResNet. AISTATS Soufiane Hayou, Eugenio Clerico, Bobby He, George Deligiannidis, Arnaud Doucet, Judith Rousseau
2021	—	`conf`	The Curse of Depth in Kernel Regime. ICBINB@NeurIPS Soufiane Hayou, Arnaud Doucet, Judith Rousseau
2020	J	`jnl`	Stable ResNet. CoRR Soufiane Hayou, Eugenio Clerico, Bobby He, George Deligiannidis, Arnaud Doucet, Judith Rousseau
2019	J	`jnl`	On the Impact of the Activation Function on Deep Neural Networks Training. CoRR Soufiane Hayou, Arnaud Doucet, Judith Rousseau
2019	A*	`conf`	On the Impact of the Activation function on Deep Neural Networks Training. ICML Soufiane Hayou, Arnaud Doucet, Judith Rousseau
2019	J	`jnl`	Sparse Networks with Core-Periphery Structure. CoRR Cian Naik, François Caron, Judith Rousseau
2019	J	`jnl`	Training Dynamics of Deep Networks using Stochastic Gradient Descent via Neural Tangent Kernel. CoRR Soufiane Hayou, Arnaud Doucet, Judith Rousseau
2018	J	`jnl`	On the Selection of Initialization and Activation Function for Deep Neural Networks. CoRR Soufiane Hayou, Arnaud Doucet, Judith Rousseau
2009	J	`jnl`	Bayesian hidden Markov model for DNA sequence segmentation: A prior sensitivity analysis. Comput. Stat. Data Anal. Darfiana Nur, David Allingham, Judith Rousseau, Kerrie L. Mengersen, Ross McVinish