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20232025
most citedMarginal Density Ratio for Off-Policy Evaluation in Contextual Bandits

1 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2025

Control Variate Score Matching for Diffusion Models

Khaled Kahouli, Romuald Elie, Klaus-Robert Müller +3

Sampling from unnormalized probability densities is a pervasive challenge across the computational and physical sciences. Diffusion models provide a powerful generative framework f…

cs.SD2025

Source Separation by Flow Matching

Robin Scheibler, John R. Hershey, Arnaud Doucet +1

We consider the problem of single-channel audio source separation with the goal of reconstructing sources from their mixture. We address this ill-posed problem with FLOSS (FLOw…

math.ST2025

On the Asymptotics of Importance Weighted Variational Inference

Badr-Eddine Cherief-Abdellatif, Randal Douc, Arnaud Doucet +1

For complex latent variable models, the likelihood function is not available in closed form. In this context, a popular method to perform parameter estimation is Importance Weighte…

stat.CO2024

Optimised Annealed Sequential Monte Carlo Samplers

Saifuddin Syed, Alexandre Bouchard-Côté, Kevin Chern +1

Annealed Sequential Monte Carlo (ASMC) samplers are special cases of SMC samplers where the sequence of distributions can be embedded in a smooth path of distributions. Using this…

stat.ML2023★ 1 cited

Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits

Muhammad Faaiz Taufiq, Arnaud Doucet, Rob Cornish +1

Off-Policy Evaluation (OPE) in contextual bandits is crucial for assessing new policies using existing data without costly experimentation. However, current OPE methods, such as In…

stat.ME2023★ 1 cited

An energy-based model approach to rare event probability estimation

Lea Friedli, David Ginsbourger, Arnaud Doucet +1

The estimation of rare event probabilities plays a pivotal role in diverse fields. Our aim is to determine the probability of a hazard or system failure occurring when a quantity o…

cs.LG2023

Diffusion Generative Inverse Design

Marin Vlastelica, Tatiana López-Guevara, Kelsey Allen +3

Inverse design refers to the problem of optimizing the input of an objective function in order to enact a target outcome. For many real-world engineering problems, the objective fu…