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Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives

9 October 2018

Papers citing "Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives"

29 / 29 papers shown

Title
Scalable Robust Bayesian Co-Clustering with Compositional ELBOs Ashwin Vinod Chandrajit Bajaj BDL 108 0 0 05 Apr 2025
Generative Adversarial Networks for High-Dimensional Item Factor Analysis: A Deep Adversarial Learning Algorithm Nanyu Luo Feng Ji DRL 76 0 0 15 Feb 2025
SoftCVI: Contrastive variational inference with self-generated soft labels Daniel Ward Mark Beaumont Matteo Fasiolo BDL 206 1 0 22 Jul 2024
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 497 10,591 0 17 Feb 2020
Pathwise Derivatives for Multivariate Distributions M. Jankowiak Theofanis Karaletsos 112 11 0 05 Jun 2018
Pathwise Derivatives Beyond the Reparameterization Trick M. Jankowiak F. Obermeyer 145 113 0 05 Jun 2018
Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow T. Le Adam R. Kosiorek N. Siddharth Yee Whye Teh Frank Wood BDL 56 23 0 26 May 2018
Implicit Reparameterization Gradients Michael Figurnov S. Mohamed A. Mnih BDL 105 234 0 22 May 2018
World Models David R Ha Jürgen Schmidhuber SyDa 146 1,098 0 27 Mar 2018
Stochastic Video Generation with a Learned Prior Emily L. Denton Rob Fergus VGen 96 526 0 21 Feb 2018
Tighter Variational Bounds are Not Necessarily Better Tom Rainforth Adam R. Kosiorek T. Le Chris J. Maddison Maximilian Igl Frank Wood Yee Whye Teh DRL 172 198 0 13 Feb 2018
Stochastic Variational Video Prediction Mohammad Babaeizadeh Chelsea Finn D. Erhan R. Campbell Sergey Levine DRL VGen 84 543 0 30 Oct 2017
Variational Sequential Monte Carlo C. A. Naesseth Scott W. Linderman Rajesh Ranganath David M. Blei BDL 263 214 0 31 May 2017
Filtering Variational Objectives Chris J. Maddison Dieterich Lawson George Tucker N. Heess Mohammad Norouzi A. Mnih Arnaud Doucet Yee Whye Teh FedML 238 210 0 25 May 2017
Online Learning Rate Adaptation with Hypergradient Descent A. G. Baydin R. Cornish David Martínez-Rubio Mark Schmidt Frank Wood ODL 83 250 0 14 Mar 2017
PixelVAE: A Latent Variable Model for Natural Images Ishaan Gulrajani Kundan Kumar Faruk Ahmed Adrien Ali Taïga Francesco Visin David Vazquez Aaron Courville DRL SSL BDL 80 340 0 15 Nov 2016
Variational Lossy Autoencoder Xi Chen Diederik P. Kingma Tim Salimans Yan Duan Prafulla Dhariwal John Schulman Ilya Sutskever Pieter Abbeel DRL SSL GAN 152 676 0 08 Nov 2016
Stochastic Backpropagation through Mixture Density Distributions Alex Graves BDL 100 44 0 19 Jul 2016
Improving Variational Inference with Inverse Autoregressive Flow Diederik P. Kingma Tim Salimans Rafal Jozefowicz Xi Chen Ilya Sutskever Max Welling BDL DRL 147 1,825 0 15 Jun 2016
Sequential Neural Models with Stochastic Layers Marco Fraccaro Søren Kaae Sønderby Ulrich Paquet Ole Winther BDL 117 398 0 24 May 2016
Variational inference for Monte Carlo objectives A. Mnih Danilo Jimenez Rezende DRL BDL 161 291 0 22 Feb 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 289 4,807 0 04 Jan 2016
Deep Kalman Filters Rahul G. Krishnan Uri Shalit David Sontag BDL AI4TS 73 374 0 16 Nov 2015
Learning Wake-Sleep Recurrent Attention Models Jimmy Ba Roger C. Grosse Ruslan Salakhutdinov B. Frey BDL 90 65 0 22 Sep 2015
Importance Weighted Autoencoders Yuri Burda Roger C. Grosse Ruslan Salakhutdinov BDL 276 1,246 0 01 Sep 2015
Neural Adaptive Sequential Monte Carlo S. Gu Zoubin Ghahramani Richard Turner BDL 76 147 0 10 Jun 2015
A Recurrent Latent Variable Model for Sequential Data Junyoung Chung Kyle Kastner Laurent Dinh Kratarth Goel Aaron Courville Yoshua Bengio DRL BDL 95 1,262 0 07 Jun 2015
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 318 4,196 0 21 May 2015
Reweighted Wake-Sleep J. Bornschein Yoshua Bengio BDL 109 183 0 11 Jun 2014