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cs.LG2025
Blade: A Derivative-free Bayesian Inversion Method using Diffusion Priors
Hongkai Zheng, Austin Wang, Zihui Wu +3
Derivative-free Bayesian inversion arises in science and engineering applications, particularly when forward model is costly or infeasible to differentiate through. Existing deriva…
cs.LG2024
Ensemble Kalman Diffusion Guidance: A Derivative-free Method for Inverse Problems
Hongkai Zheng, Wenda Chu, Austin Wang +3
When solving inverse problems, one increasingly popular approach is to use pre-trained diffusion models as plug-and-play priors. This framework can accommodate different forward mo…