34 citations · 42 across the 3 of their papers we have counts for
3 papers
Metropolis Sampling for Constrained Diffusion Models
Nic Fishman, Leo Klarner, Emile Mathieu +2
Denoising diffusion models have recently emerged as the predominant paradigm for generative modelling on image domains. In addition, their extension to Riemannian manifolds has fac…
Diffusion Models for Constrained Domains
Nic Fishman, Leo Klarner, Valentin De Bortoli +2
Denoising diffusion models are a novel class of generative algorithms that achieve state-of-the-art performance across a range of domains, including image generation and text-to-im…
GAUCHE: A Library for Gaussian Processes in Chemistry
Ryan-Rhys Griffiths, Leo Klarner, Henry B. Moss +24
We introduce GAUCHE, a library for GAUssian processes in CHEmistry. Gaussian processes have long been a cornerstone of probabilistic machine learning, affording particular advantag…