2 papers
cs.LG2026
Introduction to Stochastic Differential Equations for Generative Machine Learning: A Variational Perspective
Ole Winther, Paul Jeha, Sander Dieleman +3
The use of ordinary and stochastic differential equations has led to substantial progress in generative machine learning with applications to, for example, image, video and biomole…
cs.CV2025
Uncertainty evaluation of segmentation models for Earth observation
Melanie Rey, Andriy Mnih, Maxim Neumann +2
This paper investigates methods for estimating uncertainty in semantic segmentation predictions derived from satellite imagery. Estimating uncertainty for segmentation presents uni…