### Web: http://arxiv.org/abs/2206.11172

June 23, 2022, 1:11 a.m. | Henry Li, Yuval Kluger

Any explicit functional representation $f$ of a density is hampered by two
main obstacles when we wish to use it as a generative model: designing $f$ so
that sampling is fast, and estimating $Z = \int f$ so that $Z^{-1}f$ integrates
to 1. This becomes increasingly complicated as $f$ itself becomes complicated.
In this paper, we show that when modeling one-dimensional conditional densities
with a neural network, $Z$ can be exactly and efficiently computed by letting
the network represent the …

### Machine Learning Researcher - Saalfeld Lab

@ Howard Hughes Medical Institute - Chevy Chase, MD | Ashburn, Virginia

### Project Director, Machine Learning in US Health

@ ideas42.org | Remote, US

### Data Science Intern

@ NannyML | Remote

### Machine Learning Engineer NLP/Speech

@ Play.ht | Remote

### Research Scientist, 3D Reconstruction

@ Yembo | Remote, US

### Clinical Assistant or Associate Professor of Management Science and Systems

@ University at Buffalo | Buffalo, NY