246 citations · 1.1k across the 36 of their papers we have counts for
41 papers
Getting Your Guidance Weights Right in diffusion and flow-matching posterior sampling
Liam Moroy, Jean-François Giovannelli, Yoann Altmann +3
Training-free posterior sampling methods, also known as Plug-and-Play methods, leverage pretrained unconditional diffusion or flow-matching models to solve inverse problems. Most e…
Cross-modal learning for SAR target recognition using optical vision foundation models
Lucas Hirsch, James R. Hopgood, Javid Khan +2
Synthetic Aperture Radar (SAR) is an important modality in a wide range of imaging applications due to its versatile, long range and near all weather operating capabilities. Howeve…
Training of Spiking Neural Networks with Expectation-Propagation
Dan Yao, Steve McLaughlin, Yoann Altmann
In this paper, we propose a unifying message-passing framework for training spiking neural networks (SNNs) using Expectation-Propagation. Our gradient-free method is capable of lea…
Statistical modelling and Bayesian inversion for a Compton imaging system: application to radioactive source localisation
Cecilia Tarpau, Ming Fang, Konstantinos C. Zygalakis +3
This paper presents a statistical forward model for a Compton imaging system, called Compton imager. This system, under development at the University of Illinois Urbana Champaign,…
Roadmap on Nanoscale Magnetic Resonance Imaging
Raffi Budakian, Amit Finkler, Alexander Eichler +22
The field of nanoscale magnetic resonance imaging (NanoMRI) was started 30 years ago. It was motivated by the desire to image single molecules and molecular assemblies, such as pro…
Accelerated Bayesian imaging by relaxed proximal-point Langevin sampling
Teresa Klatzer, Paul Dobson, Yoann Altmann +3
This paper presents a new accelerated proximal Markov chain Monte Carlo methodology to perform Bayesian inference in imaging inverse problems with an underlying convex geometry. Th…