270 citations · 1.4k across the 97 of their papers we have counts for
8 papers · 1 filter
Local MAP Sampling for Diffusion Models
Shaorong Zhang, Rob Brekelmans, Greg Ver Steeg
Diffusion Posterior Sampling (DPS) provides a principled Bayesian approach to inverse problems by sampling from . While posterior sampling is valuable for capturing…
FedDAPL: Toward Client-Private Generalization in Federated Learning
Soroosh Safari Loaliyan, Jose-Luis Ambite, Paul M. Thompson +2
Federated Learning (FL) trains models locally at each research center or clinic and aggregates only model updates, making it a natural fit for medical imaging, where strict privacy…
MMG: Mutual Information Estimation via the MMSE Gap in Diffusion
Longxuan Yu, Xing Shi, Xianghao Kong +2
Mutual information (MI) is one of the most general ways to measure relationships between random variables, but estimating this quantity for complex systems is challenging. Denoisin…
Measurement-Aligned Sampling for Inverse Problem
Shaorong Zhang, Rob Brekelmans, Yunshu Wu +1
Diffusion models provide a powerful way to incorporate complex prior information for solving inverse problems. However, existing methods struggle to correctly incorporate guidance…
AbFlowNet: Optimizing Antibody-Antigen Binding Energy via Diffusion-GFlowNet Fusion
Abrar Rahman Abir, Haz Sameen Shahgir, Md Rownok Zahan Ratul +3
Complementarity Determining Regions (CDRs) are critical segments of an antibody that facilitate binding to specific antigens. Current computational methods for CDR design utilize r…
Diffusion Bridge Models for 3D Medical Image Translation
Shaorong Zhang, Tamoghna Chattopadhyay, Sophia I. Thomopoulos +3
Diffusion tensor imaging (DTI) provides crucial insights into the microstructure of the human brain, but it can be time-consuming to acquire compared to more readily available T1-w…