Reinterpreting Importance-Weighted Autoencoders

10 April 2017

Papers citing "Reinterpreting Importance-Weighted Autoencoders"

34 / 34 papers shown

Title
Improving Variational Autoencoder Estimation from Incomplete Data with Mixture Variational Families Vaidotas Šimkus Michael U. Gutmann 48 2 0 05 Mar 2024
Reparameterized Variational Rejection Sampling M. Jankowiak Du Phan DRL BDL 24 1 0 26 Sep 2023
Massively Parallel Reweighted Wake-Sleep Thomas Heap Gavin Leech Laurence Aitchison BDL 24 2 0 18 May 2023
U-Statistics for Importance-Weighted Variational Inference Javier Burroni Kenta Takatsu Justin Domke Daniel Sheldon 18 1 0 27 Feb 2023
Tighter Variational Bounds are Not Necessarily Better. A Research Report on Implementation, Ablation Study, and Extensions Amine MĆharrak Vít Ruzicka Sangyun Shin M. Vankadari DRL 16 0 0 23 Sep 2022
Latent Variable Modelling Using Variational Autoencoders: A survey Vasanth Kalingeri CML DRL 26 2 0 20 Jun 2022
Variational Sparse Coding with Learned Thresholding Kion Fallah Christopher Rozell DRL 36 7 0 07 May 2022
Variational Inference with Locally Enhanced Bounds for Hierarchical Models Tomas Geffner Justin Domke 29 5 0 08 Mar 2022
Variational methods for simulation-based inference Manuel Glöckler Michael Deistler Jakob H. Macke 32 47 0 08 Mar 2022
Surrogate Likelihoods for Variational Annealed Importance Sampling M. Jankowiak Du Phan BDL 35 13 0 22 Dec 2021
Scalable Multi-Task Gaussian Processes with Neural Embedding of Coregionalization Haitao Liu Jiaqi Ding Xinyu Xie Xiaomo Jiang Yusong Zhao Xiaofang Wang BDL 34 14 0 20 Sep 2021
MCMC Variational Inference via Uncorrected Hamiltonian Annealing Tomas Geffner Justin Domke 33 34 0 08 Jul 2021
Decomposed Mutual Information Estimation for Contrastive Representation Learning Alessandro Sordoni Nouha Dziri Hannes Schulz Geoffrey J. Gordon Philip Bachman Rémi Tachet des Combes SSL 24 30 0 25 Jun 2021
NEO: Non Equilibrium Sampling on the Orbit of a Deterministic Transform Achille Thin Yazid Janati Sylvain Le Corff Charles Ollion Arnaud Doucet Alain Durmus Eric Moulines C. Robert 35 7 0 17 Mar 2021
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding Yangjun Ruan Karen Ullrich Daniel de Souza Severo James Townsend Ashish Khisti Arnaud Doucet Alireza Makhzani Chris J. Maddison 11 25 0 22 Feb 2021
Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference M. Vandegar Michael Kagan Antoine Wehenkel Gilles Louppe 34 27 0 11 Nov 2020
Failure Modes of Variational Autoencoders and Their Effects on Downstream Tasks Yaniv Yacoby Weiwei Pan Finale Doshi-Velez CML DRL 32 25 0 14 Jul 2020
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference Rob Brekelmans Vaden Masrani Frank Wood Greg Ver Steeg Aram Galstyan 22 16 0 01 Jul 2020
Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization Abhinav Agrawal Daniel Sheldon Justin Domke TPM BDL 19 38 0 18 Jun 2020
Learning Continuous-Time Dynamics by Stochastic Differential Networks Yingru Liu Yucheng Xing Xuewen Yang Xin Wang Jing Shi Di Jin Zhaoyue Chen BDL 26 6 0 11 Jun 2020
NestedVAE: Isolating Common Factors via Weak Supervision M. Vowels Necati Cihan Camgöz Richard Bowden CML DRL 26 21 0 26 Feb 2020
Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models Yuge Shi Siddharth Narayanaswamy Brooks Paige Philip Torr DRL 32 266 0 08 Nov 2019
Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation Justin Domke Daniel Sheldon 26 18 0 24 Jun 2019
Streaming Variational Monte Carlo Yuan Zhao Josue Nassar I. Jordan M. Bugallo Il Memming Park BDL 34 21 0 04 Jun 2019
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Pierre-Alexandre Mattei J. Frellsen SyDa 25 45 0 06 Dec 2018
The Variational Deficiency Bottleneck P. Banerjee Guido Montúfar 15 7 0 27 Oct 2018
Active Learning based on Data Uncertainty and Model Sensitivity Nutan Chen Alexej Klushyn A. Paraschos Djalel Benbouzid Patrick van der Smagt 21 17 0 06 Aug 2018
Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers Marcel Hirt P. Dellaportas BDL 20 10 0 23 May 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 25 197 0 13 Feb 2018
Inference Suboptimality in Variational Autoencoders Chris Cremer Xuechen Li David Duvenaud DRL BDL 33 280 0 10 Jan 2018
Faithful Inversion of Generative Models for Effective Amortized Inference Stefan Webb Adam Goliñski R. Zinkov Siddharth Narayanaswamy Tom Rainforth Yee Whye Teh Frank Wood TPM 51 46 0 01 Dec 2017
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 38 684 0 15 Nov 2017
Metrics for Deep Generative Models Nutan Chen Alexej Klushyn Richard Kurle Xueyan Jiang Justin Bayer Patrick van der Smagt SyDa DRL 31 116 0 03 Nov 2017
Variational Sequential Monte Carlo C. A. Naesseth Scott W. Linderman Rajesh Ranganath David M. Blei BDL 32 214 0 31 May 2017