Pathwise Derivatives Beyond the Reparameterization Trick

5 June 2018

Papers citing "Pathwise Derivatives Beyond the Reparameterization Trick"

13 / 13 papers shown

Title
Analytical Approximation of the ELBO Gradient in the Context of the Clutter Problem Roumen Nikolaev Popov 29 0 0 16 Apr 2024
Reparameterized Variational Rejection Sampling M. Jankowiak Du Phan DRL BDL 24 1 0 26 Sep 2023
Gradients should stay on Path: Better Estimators of the Reverse- and Forward KL Divergence for Normalizing Flows Lorenz Vaitl K. Nicoli Shinichi Nakajima Pan Kessel 61 24 0 17 Jul 2022
Is Automated Topic Model Evaluation Broken?: The Incoherence of Coherence Alexander Miserlis Hoyle Pranav Goel Denis Peskov Andrew Hian-Cheong Jordan L. Boyd-Graber Philip Resnik 41 127 0 05 Jul 2021
Differentiable Particle Filtering without Modifying the Forward Pass Adam Scibior Frank D. Wood 28 19 0 18 Jun 2021
Dirichlet Pruning for Neural Network Compression Kamil Adamczewski Mijung Park 27 3 0 10 Nov 2020
Statistical Guarantees for Transformation Based Models with Applications to Implicit Variational Inference Sean Plummer Shuang Zhou A. Bhattacharya David B. Dunson D. Pati DRL 13 2 0 23 Oct 2020
Bayesian Attention Modules Xinjie Fan Shujian Zhang Bo Chen Mingyuan Zhou 117 59 0 20 Oct 2020
Flexible mean field variational inference using mixtures of non-overlapping exponential families J. Spence 17 4 0 14 Oct 2020
Adversarial Attacks on Probabilistic Autoregressive Forecasting Models Raphaël Dang-Nhu Gagandeep Singh Pavol Bielik Martin Vechev AI4TS AAML 36 20 0 08 Mar 2020
PAC-Bayes with Backprop Omar Rivasplata Vikram Tankasali Csaba Szepesvári 21 49 0 19 Aug 2019
Monte Carlo Gradient Estimation in Machine Learning S. Mohamed Mihaela Rosca Michael Figurnov A. Mnih 43 397 0 25 Jun 2019
Stochastic Backpropagation through Mixture Density Distributions Alex Graves BDL 51 44 0 19 Jul 2016