%0 Generic %1 alemi2018therml %A Alemi, Alexander A. %A Fischer, Ian %D 2018 %K 2019 arxiv google iclr machine-learning paper %T TherML: Thermodynamics of Machine Learning %U http://arxiv.org/abs/1807.04162 %X 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.

@misc{alemi2018therml, abstract = {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.}, added-at = {2019-10-07T11:35:18.000+0200}, author = {Alemi, Alexander A. and Fischer, Ian}, biburl = {https://www.bibsonomy.org/bibtex/233c092bac4cb8bf590111a6ffebc7a46/analyst}, description = {[1807.04162] TherML: Thermodynamics of Machine Learning}, interhash = {e7b99adfb92cff7875934f5bdbfe3b78}, intrahash = {33c092bac4cb8bf590111a6ffebc7a46}, keywords = {2019 arxiv google iclr machine-learning paper}, note = {cite arxiv:1807.04162Comment: Presented at the ICML 2018 workshop on Theoretical Foundations and Applications of Deep Generative Models}, timestamp = {2019-10-07T11:35:18.000+0200}, title = {TherML: Thermodynamics of Machine Learning}, url = {http://arxiv.org/abs/1807.04162}, year = 2018 }