Machine learning in and out of equilibrium

6 June 2023

Papers citing "Machine learning in and out of equilibrium"

8 / 8 papers shown

Title
The Limiting Dynamics of SGD: Modified Loss, Phase Space Oscillations, and Anomalous Diffusion D. Kunin Javier Sagastuy-Breña Lauren Gillespie Eshed Margalit Hidenori Tanaka Surya Ganguli Daniel L. K. Yamins 81 20 0 19 Jul 2021
Fluctuation-dissipation relations for stochastic gradient descent Sho Yaida 104 75 0 28 Sep 2018
Unsupervised Learning by Competing Hidden Units Dmitry Krotov J. Hopfield SSL 71 168 0 26 Jun 2018
A high-bias, low-variance introduction to Machine Learning for physicists Pankaj Mehta Marin Bukov Ching-Hao Wang A. G. Day C. Richardson Charles K. Fisher D. Schwab AI4CE 108 879 0 23 Mar 2018
Visualizing the Loss Landscape of Neural Nets Hao Li Zheng Xu Gavin Taylor Christoph Studer Tom Goldstein 266 1,901 0 28 Dec 2017
Three Factors Influencing Minima in SGD Stanislaw Jastrzebski Zachary Kenton Devansh Arpit Nicolas Ballas Asja Fischer Yoshua Bengio Amos Storkey 80 463 0 13 Nov 2017
Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks Pratik Chaudhari Stefano Soatto MLT 73 304 0 30 Oct 2017
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,364 0 22 Dec 2014