3 papers
cs.LG2026
Iterative Importance Fine-tuning of Diffusion Models
Alexander Denker, Shreyas Padhy, Francisco Vargas +1
Diffusion models are an important tool for generative modelling, serving as effective priors in applications such as imaging and protein design. A key challenge in applying diffusi…
cs.LG2025
DEFT: Efficient Fine-Tuning of Diffusion Models by Learning the Generalised -transform
Alexander Denker, Francisco Vargas, Shreyas Padhy +7
Generative modelling paradigms based on denoising diffusion processes have emerged as a leading candidate for conditional sampling in inverse problems. In many real-world applicati…
stat.ML2025
Transport meets Variational Inference: Controlled Monte Carlo Diffusions
Francisco Vargas, Shreyas Padhy, Denis Blessing +1
Connecting optimal transport and variational inference, we present a principled and systematic framework for sampling and generative modelling centred around divergences on path sp…