{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/mine-mutual-information-neural-estimation","title":"MINE: Mutual Information Neural Estimation","arxiv_id":"1801.04062","date":"2018-01-12","proceeding":null,"authors":["Mohamed Ishmael Belghazi","Aristide Baratin","Sai Rajeswar","Sherjil Ozair","Yoshua Bengio","Aaron Courville","R. Devon Hjelm"],"abstract":"We argue that the estimation of mutual information between high dimensional continuous random variables can be achieved by gradient descent over neural networks. 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