output
20022026
most citedA regression-based Monte Carlo method to solve backward stochastic differential equations

425 citations

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19 papers · 1 filter

stat.ML2025

Improving the evaluation of samplers on multi-modal targets

Louis Grenioux, Maxence Noble, Marylou Gabrié

Addressing multi-modality constitutes one of the major challenges of sampling. In this reflection paper, we advocate for a more systematic evaluation of samplers towards two source…

stat.ML20241 cited

Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels

Raphaël Carpintero Perez, Sébastien da Veiga, Josselin Garnier +1

Supervised learning has recently garnered significant attention in the field of computational physics due to its ability to effectively extract complex patterns for tasks like solv…

stat.ML2024

Incentivized Learning in Principal-Agent Bandit Games

Antoine Scheid, Daniil Tiapkin, Etienne Boursier +5

This work considers a repeated principal-agent bandit game, where the principal can only interact with her environment through the agent. The principal and the agent have misaligne…

stat.ML20231 cited

Conformal Prediction with Missing Values

Margaux Zaffran, Aymeric Dieuleveut, Julie Josse +1

Conformal prediction is a theoretically grounded framework for constructing predictive intervals. We study conformal prediction with missing values in the covariates -- a setting t…

stat.ML20222 cited

Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms

Vincent Plassier, Alain Durmus, Eric Moulines

This paper focuses on Bayesian inference in a federated learning context (FL). While several distributed MCMC algorithms have been proposed, few consider the specific limitations o…

stat.ML2022

Sparse tree-based initialization for neural networks

Patrick Lutz, Ludovic Arnould, Claire Boyer +1

Dedicated neural network (NN) architectures have been designed to handle specific data types (such as CNN for images or RNN for text), which ranks them among state-of-the-art metho…