Handling the Positive-Definite Constraint in the Bayesian Learning Rule

24 February 2020

Papers citing "Handling the Positive-Definite Constraint in the Bayesian Learning Rule"

8 / 8 papers shown

Title
Spectral-factorized Positive-definite Curvature Learning for NN Training Wu Lin Felix Dangel Runa Eschenhagen Juhan Bae Richard E. Turner Roger B. Grosse 47 0 0 10 Feb 2025
Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space Michael Diao Krishnakumar Balasubramanian Sinho Chewi Adil Salim BDL 18 20 0 10 Apr 2023
Bayesian Learning for Neural Networks: an algorithmic survey M. Magris Alexandros Iosifidis BDL DRL 35 68 0 21 Nov 2022
Manifold Gaussian Variational Bayes on the Precision Matrix M. Magris M. Shabani Alexandros Iosifidis 37 2 0 26 Oct 2022
A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models O. Arenz Philipp Dahlinger Zihan Ye Michael Volpp Gerhard Neumann 39 15 0 23 Sep 2022
Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees William J. Wilkinson Simo Särkkä Arno Solin BDL 21 15 0 02 Nov 2021
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 74 266 0 13 Jun 2018
A Stein variational Newton method Gianluca Detommaso Tiangang Cui Alessio Spantini Youssef Marzouk Robert Scheichl 61 114 0 08 Jun 2018