collaborators

7 papers

stat.ML2026

Twisted Schrödinger Bridge Matching

Maxence Noble, Marie Scheid, Yazid Janati +2

Over the past few years, diffusion-based Schrödinger bridge models have been proposed to approximate optimal transport dynamics between two prescribed boundary distributions, with…

cs.LG2026

Bayesian Rain Field Reconstruction using Commercial Microwave Links and Diffusion Model Priors

Badr Moufad, Albina Ilina, Hai Victor Habi +4

Commercial Microwave Links (CMLs) offer dense spatial coverage for rainfall sensing but produce path-integrated measurements that make accurate ground-level reconstruction challeng…

cs.CV2026

Efficient Zero-Shot Inpainting with Decoupled Diffusion Guidance

Badr Moufad, Navid Bagheri Shouraki, Alain Oliviero Durmus +4

Diffusion models have emerged as powerful priors for image editing tasks such as inpainting and local modification, where the objective is to generate realistic content that remain…

cs.CV2026

When Test-Time Guidance Is Enough: Fast Image and Video Editing with Diffusion Guidance

Ahmed Ghorbel, Badr Moufad, Navid Bagheri Shouraki +5

Text-driven image and video editing can be naturally cast as inpainting problems, where masked regions are reconstructed to remain consistent with both the observed content and the…

cs.LG2026

Categorical Reparameterization with Denoising Diffusion models

Samson Gourevitch, Alain Durmus, Eric Moulines +2

Learning models with categorical variables requires optimizing expectations over discrete distributions, a setting in which stochastic gradient-based optimization is challenging du…

stat.ML2026

Fast and Robust Likelihood-Guided Diffusion Posterior Sampling with Amortized Variational Inference

Léon Zheng, Thomas Hirtz, Yazid Janati +1

Zero-shot diffusion posterior sampling offers a flexible framework for inverse problems by accommodating arbitrary degradation operators at test time, but incurs high computational…