ISIW implements Inverse Sampling Intensity Weighting (ISIW) for adjusting geostatistical models under preferential sampling (PS). The method is introduced in: Hsiao, T. W. and Waller, L. A. (2025).

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 ...

️Flow matching is a recent state-of-the-art framework for generative modeling based on ordinary differential equations (ODEs). While closely related to diffusion models, it provides a more general ...

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.