FunMC: A functional API for building Markov Chains
Computation
2021-05-27 v3
Abstract
Constant-memory algorithms, also loosely called Markov chains, power the vast majority of probabilistic inference and machine learning applications today. A lot of progress has been made in constructing user-friendly APIs around these algorithms. Such APIs, however, rarely make it easy to research new algorithms of this type. In this work we present FunMC, a minimal Python library for doing methodological research into algorithms based on Markov chains. FunMC is not targeted toward data scientists or others who wish to use MCMC or optimization as a black box, but rather towards researchers implementing new Markovian algorithms from scratch.
Cite
@article{arxiv.2001.05035,
title = {FunMC: A functional API for building Markov Chains},
author = {Pavel Sountsov and Alexey Radul and Srinivas Vasudevan},
journal= {arXiv preprint arXiv:2001.05035},
year = {2021}
}
Comments
Updated source code to reflect API; updated link to point to new location