arXiv Analytics

Sign in

arXiv:1807.04162 [cs.LG]AbstractReferencesReviewsResources

TherML: Thermodynamics of Machine Learning

Alexander A. Alemi, Ian Fischer

Published 2018-07-11Version 1

In this work we offer a framework for reasoning about a wide class of existing objectives in machine learning. We develop a formal correspondence between this work and thermodynamics and discuss its implications.

Comments: Presented at the ICML 2018 workshop on Theoretical Foundations and Applications of Deep Generative Models
Related articles: Most relevant | Search more
arXiv:1808.00931 [cs.LG] (Published 2018-08-02)
Machine Learning of Space-Fractional Differential Equations
arXiv:1506.00976 [cs.LG] (Published 2015-06-02)
Toward a generic representation of random variables for machine learning
arXiv:1811.07216 [cs.LG] (Published 2018-11-17, updated 2018-11-24)
Machine Learning for Health (ML4H) Workshop at NeurIPS 2018