3 papers
stat.ML2026
Conditional flow matching for physics-constrained inverse problems with finite training data
Agnimitra Dasgupta, Ali Fardisi, Mehrnegar Aminy +4
This study presents a conditional flow matching framework for solving physics-constrained Bayesian inverse problems. In this setting, samples from the joint distribution of inferre…
stat.ML2026
Closed-form conditional diffusion models for data assimilation
Brianna Binder, Agnimitra Dasgupta, Assad Oberai
We propose closed-form conditional diffusion models for data assimilation. Diffusion models use data to learn the score function (defined as the gradient of the log-probability den…
cs.LG2026
Probabilistic Forecasting of Localized Wildfire Spread Based on Conditional Flow Matching
Bryan Shaddy, Haitong Qin, Brianna Binder +4
This study presents a probabilistic surrogate model for localized wildfire spread based on a conditional flow matching algorithm. The approach models fire progression as a stochast…