activity
20242026
collaborators

5 papers

stat.ML2026

A Mean-Field Framework for Inference-Time Distributional Control of Diffusion Models

Samuel Howard, Nikolas Nüsken

Diffusion models are increasingly used as controllable samplers, whose generations can be steered at inference time according to a chosen reward function. While such rewards are ty…

stat.ML2025

Control Consistency Losses for Diffusion Bridges

Samuel Howard, Nikolas Nüsken, Jakiw Pidstrigach

Simulating the conditioned dynamics of diffusion processes, given their initial and terminal states, is an important but challenging problem in the sciences. The difficulty is part…

cs.LG2025

Diffusion Models and the Manifold Hypothesis: Log-Domain Smoothing is Geometry Adaptive

Tyler Farghly, Peter Potaptchik, Samuel Howard +2

Diffusion models have achieved state-of-the-art performance, demonstrating remarkable generalisation capabilities across diverse domains. However, the mechanisms underpinning these…

stat.ML2025

Schrödinger Bridge Matching for Tree-Structured Costs and Entropic Wasserstein Barycentres

Samuel Howard, Peter Potaptchik, George Deligiannidis

Recent advances in flow-based generative modelling have provided scalable methods for computing the Schrödinger Bridge (SB) between distributions, a dynamic form of entropy-regular…

stat.ML2024

Differentiable Cost-Parameterized Monge Map Estimators

Samuel Howard, George Deligiannidis, Patrick Rebeschini +1

Within the field of optimal transport (OT), the choice of ground cost is crucial to ensuring that the optimality of a transport map corresponds to usefulness in real-world applicat…