A Free-Energy Principle for Representation Learning

27 February 2020

Papers citing "A Free-Energy Principle for Representation Learning"

8 / 8 papers shown

Title
Computational Optimal Transport Gabriel Peyré Marco Cuturi OT 140 2,133 0 01 Mar 2018
Stochastic Gradient Descent as Approximate Bayesian Inference Stephan Mandt Matthew D. Hoffman David M. Blei BDL 44 594 0 13 Apr 2017
Overcoming catastrophic forgetting in neural networks J. Kirkpatrick Razvan Pascanu Neil C. Rabinowitz J. Veness Guillaume Desjardins ... A. Grabska-Barwinska Demis Hassabis Claudia Clopath D. Kumaran R. Hadsell CLL 268 7,410 0 02 Dec 2016
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys Pratik Chaudhari A. Choromańska Stefano Soatto Yann LeCun Carlo Baldassi C. Borgs J. Chayes Levent Sagun R. Zecchina ODL 84 769 0 06 Nov 2016
Identity Mappings in Deep Residual Networks Kaiming He Xinming Zhang Shaoqing Ren Jian Sun 288 10,149 0 16 Mar 2016
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 367 16,962 0 20 Dec 2013
A PAC-Bayesian Tutorial with A Dropout Bound David A. McAllester 58 140 0 08 Jul 2013
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances Marco Cuturi OT 135 4,210 0 04 Jun 2013