Abstract: In recent years, the ascendance of diffusion modeling as a state-of-the-art generative modeling approach has spurred significant interest in their use as priors in Bayesian inverse problems.

Abstract: A new modeling framework integrating Ramer-Douglas-Peucker (RDP) non-uniform sampling (NUS) with a Long Short-Term Memory (LSTM)-Fully Connected Network (FCN) hybrid neural network (LFN) is ...