Natural Langevin Dynamics for Neural Networks

4 December 2017

Papers citing "Natural Langevin Dynamics for Neural Networks"

10 / 10 papers shown

Title
The Universality Lens: Why Even Highly Over-Parametrized Models Learn Well M. Feder Ruediger Urbanke Yaniv Fogel 16 0 0 09 Jun 2025
Bayes Complexity of Learners vs Overfitting Grzegorz Gluch R. Urbanke UQCV BDL 15 1 0 13 Mar 2023
Langevin algorithms for very deep Neural Networks with application to image classification Pierre Bras 51 6 0 27 Dec 2022
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 242 1,177 0 07 Jul 2021
Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantification Gianni Franchi Andrei Bursuc Emanuel Aldea Séverine Dubuisson Isabelle Bloch BDL UQCV 94 27 0 04 Dec 2020
Natural-gradient learning for spiking neurons Elena Kreutzer Walter Senn Mihai A. Petrovici 48 13 0 23 Nov 2020
Riemannian batch normalization for SPD neural networks Daniel A. Brooks Olivier Schwander F. Barbaresco J. Schneider Matthieu Cord 98 93 0 03 Sep 2019
Adaptively Preconditioned Stochastic Gradient Langevin Dynamics C. A. Bhardwaj ODL 31 9 0 10 Jun 2019
Fluctuation-dissipation relations for stochastic gradient descent Sho Yaida 113 75 0 28 Sep 2018
Stochastic natural gradient descent draws posterior samples in function space Samuel L. Smith Daniel Duckworth Semon Rezchikov Quoc V. Le Jascha Narain Sohl-Dickstein BDL 85 6 0 25 Jun 2018