Web: http://arxiv.org/abs/2107.13735

May 5, 2022, 1:11 a.m. | Yubin Lu, Romit Maulik, Ting Gao, Felix Dietrich, Ioannis G. Kevrekidis, Jinqiao Duan

stat.ML updates on arXiv.org arxiv.org

In this work, we propose a method to learn multivariate probability
distributions using sample path data from stochastic differential equations.
Specifically, we consider temporally evolving probability distributions (e.g.,
those produced by integrating local or nonlocal Fokker-Planck equations). We
analyze this evolution through machine learning assisted construction of a
time-dependent mapping that takes a reference distribution (say, a Gaussian) to
each and every instance of our evolving distribution. If the reference
distribution is the initial condition of a Fokker-Planck equation, what …

arxiv evolution learning ml

More from arxiv.org / stat.ML updates on arXiv.org

Data Analyst, Patagonia Action Works

@ Patagonia | Remote

Data & Insights Strategy & Innovation General Manager

@ Chevron Services Company, a division of Chevron U.S.A Inc. | Houston, TX

Faculty members in Research areas such as Bayesian and Spatial Statistics; Data Privacy and Security; AI/ML; NLP; Image and Video Data Analysis

@ Ahmedabad University | Ahmedabad, India

Director, Applied Mathematics & Computational Research Division

@ Lawrence Berkeley National Lab | Berkeley, Ca

Business Data Analyst

@ MainStreet Family Care | Birmingham, AL

Assistant/Associate Professor of the Practice in Business Analytics

@ Georgetown University McDonough School of Business | Washington DC