AISTATS 2022poster4 citations
Estimators of Entropy and Information via Inference in Probabilistic Models
Feras Saad, Marco Cusumano-Towner, Vikash Mansinghka
Abstract
Estimating information-theoretic quantities such as entropy and mutual information is central to many problems in statistics and machine learning, but challenging in high dimensions. This paper presents
BibTeX
@InProceedings{pmlr-v151-saad22a,
title = { Estimators of Entropy and Information via Inference in Probabilistic Models },
author = {Saad, Feras and Cusumano-Towner, Marco and Mansinghka, Vikash},
booktitle = {Proceedings of The 25th International Conference on Artificial Intelligence and Statistics},
pages = {5604--5621},
year = {2022},
editor = {Camps-Valls, Gustau and Ruiz, Francisco J. R. and Valera, Isabel},
volume = {151},
series = {Proceedings of Machine Learning Research},
month = {28--30 Mar},
publisher = {PMLR},
pdf = {https://proceedings.mlr.press/v151/saad22a/saad22a.pdf},
url = {https://proceedings.mlr.press/v151/saad22a.html},
abstract = { Estimating information-theoretic quantities such as entropy and mutual information is central to many problems in statistics and machine learning, but challenging in high dimensions. This paper presents