7 papers
Probabilistic Zeeman-Doppler imaging of stellar magnetic fields: I. Analysis of tau Scorpii in the weak-field limit
Jennifer Rosina Andersson, Oleg Kochukhov, Zheng Zhao +1
Zeeman-Doppler imaging (ZDI) is used to study the surface magnetic field topology of stars, based on high-resolution spectropolarimetric time series observations. Multiple ZDI inve…
Taming Diffusion Models for Image Restoration: A Review
Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao +2
Diffusion models have achieved remarkable progress in generative modelling, particularly in enhancing image quality to conform to human preferences. Recently, these models have als…
Conditional sampling within generative diffusion models
Zheng Zhao, Ziwei Luo, Jens Sjölund +1
Generative diffusions are a powerful class of Monte Carlo samplers that leverage bridging Markov processes to approximate complex, high-dimensional distributions, such as those fou…
Conditioning diffusion models by explicit forward-backward bridging
Adrien Corenflos, Zheng Zhao, Simo Särkkä +2
Given an unconditional diffusion model targeting a joint model , using it to perform conditional simulation is still largely an open question and is typicall…
Photo-Realistic Image Restoration in the Wild with Controlled Vision-Language Models
Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao +2
Though diffusion models have been successfully applied to various image restoration (IR) tasks, their performance is sensitive to the choice of training datasets. Typically, diffus…
On Feynman--Kac training of partial Bayesian neural networks
Zheng Zhao, Sebastian Mair, Thomas B. Schön +1
Recently, partial Bayesian neural networks (pBNNs), which only consider a subset of the parameters to be stochastic, were shown to perform competitively with full Bayesian neural n…