Stein’s Method in Stochastic Geometry, Statistical Learning, and Optimisation
Abstract
Stein’s method, a powerful tool rooted in probability and stochastic analysis, has recently showcased its efficacy in addressing diverse challenges encountered in deep learning, optimisation, sampling, and causal inference. The primary focus of the workshop is to strengthen the probabilistic and analytic foundations of Stein’s method, while simultaneously exploring novel avenues for its application. Bringing together researchers from the analysis, probability, statistics, and machine learning communities, who share a common interest in Stein’s method, the workshop aims to facilitate idea exchange, tackle open problems, and foster collaborations to advance the forefront of knowledge in these fields. Of particular importance is the emphasis placed on the intersection of these disciplines, where Stein’s method plays a pivotal role.
Fields of Study & Subjects
Probability and Statistical Research
Point processes and geometric inequalities
Markov Chains and Monte Carlo Methods
Publication details
- Journal / source
- Oberwolfach Reports
- Volume
- 22
- Issue
- 3
- Pages
- 2125–2140
- Publication date
- 16 February 2026
- Language
- EN