Stochastic gradient variational Bayes for gamma approximating distributions

4 September 2015

Papers citing "Stochastic gradient variational Bayes for gamma approximating distributions"

12 / 12 papers shown

Title
DeepStability: A Study of Unstable Numerical Methods and Their Solutions in Deep Learning Eliska Kloberdanz Kyle G. Kloberdanz Wei Le 30 15 0 07 Feb 2022
A Hierarchical Variational Neural Uncertainty Model for Stochastic Video Prediction Moitreya Chatterjee Narendra Ahuja A. Cherian UQCV VGen BDL 42 17 0 06 Oct 2021
Dirichlet Pruning for Neural Network Compression Kamil Adamczewski Mijung Park 27 3 0 10 Nov 2020
Deep Autoencoding Topic Model with Scalable Hybrid Bayesian Inference Hao Zhang Bo Chen Yulai Cong D. Guo Hongwei Liu Mingyuan Zhou BDL 24 27 0 15 Jun 2020
Handling the Positive-Definite Constraint in the Bayesian Learning Rule Wu Lin Mark W. Schmidt Mohammad Emtiyaz Khan BDL 39 35 0 24 Feb 2020
Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes Creighton Heaukulani Mark van der Wilk BDL 32 15 0 22 Jun 2019
Dirichlet Variational Autoencoder Weonyoung Joo Wonsung Lee Sungrae Park Il-Chul Moon BDL DRL 19 101 0 09 Jan 2019
Pathwise Derivatives Beyond the Reparameterization Trick M. Jankowiak F. Obermeyer 30 110 0 05 Jun 2018
Reparameterization Gradient for Non-differentiable Models Wonyeol Lee Hangyeol Yu Hongseok Yang DRL 25 30 0 01 Jun 2018
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 38 684 0 15 Nov 2017
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms C. A. Naesseth Francisco J. R. Ruiz Scott W. Linderman David M. Blei BDL 25 107 0 18 Oct 2016
Automatic Differentiation Variational Inference A. Kucukelbir Dustin Tran Rajesh Ranganath Andrew Gelman David M. Blei 38 709 0 02 Mar 2016