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seminars:stat:oct52023

Statistics Seminar
Department of Mathematics and Statistics

DATE:Thursday, October 5, 2023
TIME:1:15pm – 2:15pm
LOCATION:WH 100E
SPEAKER:Jingze Liu, Binghamton University
TITLE:High-dimensional Integration and Sampling with Normalizing Flows


Abstract

In many fields of science, high-dimensional integration is required. Numerical methods have been developed to evaluate these complex integrals. We introduce the code i-flow, a Python package that performs high-dimensional numerical integration utilizing normalizing flows. Normalizing flows are machine-learned, bijective mappings between two distributions. i-flow can also be used to sample random points according to complicated distributions in high dimensions. We compare i-flow to other algorithms for high-dimensional numerical integration and show that i-flow outperforms them for high dimensional correlated integrals.

seminars/stat/oct52023.txt · Last modified: 2023/10/01 09:13 by qyu