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From the 1 of 25 linked papers with an AI index.

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20242026
most citedSpectral Diffusion Processes

1 citations · 1 across the 11 of their papers we have counts for

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stat.ML20261 cited

Spectral Diffusion Processes

Angus Phillips, Thomas Seror, Michael Hutchinson +3

The paper introduces diffusion models for stochastic processes by representing data in a spectral domain using kernels, truncating the spectral coefficients, and modeling them with…

stat.ML2026

Self-Speculative Masked Diffusions

Andrew Campbell, Valentin De Bortoli, Jiaxin Shi +1

We present self-speculative masked diffusions, a new class of masked diffusion generative models for discrete data that require significantly fewer function evaluations to generate…

stat.ML2025

Dimension-free error estimate for diffusion model and optimal scheduling

Valentin de Bortoli, Romuald Elie, Anna Kazeykina +2

Diffusion generative models have emerged as powerful tools for producing synthetic data from an empirically observed distribution. A common approach involves simulating the time-re…

stat.ML2025

From stability of Langevin diffusion to convergence of proximal MCMC for non-log-concave sampling

Marien Renaud, Valentin De Bortoli, Arthur Leclaire +1

We consider the problem of sampling distributions stemming from non-convex potentials with Unadjusted Langevin Algorithm (ULA). We prove the stability of the discrete-time ULA to d…

stat.ML2025

Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models

Marien Renaud, Jiaming Liu, Valentin de Bortoli +2

Posterior sampling has been shown to be a powerful Bayesian approach for solving imaging inverse problems. The recent plug-and-play unadjusted Langevin algorithm (PnP-ULA) has emer…