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Operator Variational Inference

27 October 2016

Papers citing "Operator Variational Inference"

50 / 72 papers shown

Title
On Divergence Measures for Training GFlowNets Tiago da Silva Eliezer de Souza da Silva Diego Mesquita BDL 154 3 0 12 Oct 2024
Kernel Semi-Implicit Variational Inference Ziheng Cheng Longlin Yu Tianyu Xie Shiyue Zhang Cheng Zhang 57 7 0 29 May 2024
SAVAE: Leveraging the variational Bayes autoencoder for survival analysis Patricia A. Apellániz J. Parras Santiago Zazo CML DRL BDL 10 1 0 22 Dec 2023
Neural Operator Variational Inference based on Regularized Stein Discrepancy for Deep Gaussian Processes Jian Xu Shian Du Junmei Yang Qianli Ma Delu Zeng BDL 50 1 0 22 Sep 2023
Semi-Implicit Variational Inference via Score Matching Longlin Yu Chuxu Zhang 77 17 0 19 Aug 2023
Variational Inference with Gaussian Score Matching Chirag Modi C. Margossian Yuling Yao Robert Mansel Gower David M. Blei Lawrence K. Saul 83 13 0 15 Jul 2023
Black-box Coreset Variational Inference Dionysis Manousakas H. Ritter Theofanis Karaletsos BDL 61 4 0 04 Nov 2022
GFlowNets and variational inference Nikolay Malkin Salem Lahlou T. Deleu Xu Ji J. E. Hu Katie Everett Dinghuai Zhang Yoshua Bengio BDL 217 89 0 02 Oct 2022
Adversarial Bayesian Simulation YueXing Wang Veronika Rovcková GAN BDL 100 5 0 25 Aug 2022
Sliced Wasserstein Variational Inference Mingxuan Yi Song Liu 68 20 0 26 Jul 2022
Gradient-Free Kernel Stein Discrepancy Matthew A. Fisher Chris J. Oates 64 5 0 06 Jul 2022
Latent Variable Modelling Using Variational Autoencoders: A survey Vasanth Kalingeri CML DRL 63 2 0 20 Jun 2022
Measuring Sample Quality in Algorithms for Intractable Normalizing Function Problems Bokgyeong Kang John Hughes M. Haran TPM 68 1 0 10 Sep 2021
Adversarial Stein Training for Graph Energy Models Shiv Shankar BDL 44 0 0 30 Aug 2021
Neural Variational Gradient Descent L. Langosco Vincent Fortuin Heiko Strathmann BDL 111 20 0 22 Jul 2021
Stein's Method Meets Computational Statistics: A Review of Some Recent Developments Andreas Anastasiou Alessandro Barp F. Briol B. Ebner Robert E. Gaunt ... Qiang Liu Lester W. Mackey Chris J. Oates Gesine Reinert Yvik Swan 101 35 0 07 May 2021
Variational inference with a quantum computer Marcello Benedetti Brian Coyle Mattia Fiorentini M. Lubasch Matthias Rosenkranz BDL 83 38 0 11 Mar 2021
End-To-End Dilated Variational Autoencoder with Bottleneck Discriminative Loss for Sound Morphing -- A Preliminary Study Matteo Lionello Hendrik Purwins 54 0 0 19 Nov 2020
Measure Transport with Kernel Stein Discrepancy Matthew A. Fisher T. Nolan Matthew M. Graham D. Prangle Chris J. Oates OT 124 15 0 22 Oct 2020
VarGrad: A Low-Variance Gradient Estimator for Variational Inference Lorenz Richter Ayman Boustati Nikolas Nusken Francisco J. R. Ruiz Ömer Deniz Akyildiz DRL 231 54 0 20 Oct 2020
Generate High Resolution Images With Generative Variational Autoencoder Abhinav Sagar GAN DRL 28 3 0 12 Aug 2020
Stochastic Stein Discrepancies Jackson Gorham Anant Raj Lester W. Mackey 113 38 0 06 Jul 2020
Sliced Kernelized Stein Discrepancy Wenbo Gong Yingzhen Li José Miguel Hernández-Lobato 94 37 0 30 Jun 2020
Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization Shijing Si Chris J. Oates Andrew B. Duncan Lawrence Carin F. Briol BDL 58 21 0 12 Jun 2020
Bayesian Sparsification Methods for Deep Complex-valued Networks Ivan Nazarov Evgeny Burnaev BDL 36 0 0 25 Mar 2020
Generalized Bayesian Filtering via Sequential Monte Carlo Ayman Boustati Ömer Deniz Akyildiz Theodoros Damoulas A. M. Johansen 65 4 0 23 Feb 2020
Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling Will Grathwohl Kuan-Chieh Wang J. Jacobsen David Duvenaud R. Zemel 67 14 0 13 Feb 2020
A Kernel Stein Test for Comparing Latent Variable Models Heishiro Kanagawa Wittawat Jitkrittum Lester W. Mackey Kenji Fukumizu Arthur Gretton 88 13 0 01 Jul 2019
Monte Carlo Gradient Estimation in Machine Learning S. Mohamed Mihaela Rosca Michael Figurnov A. Mnih 94 416 0 25 Jun 2019
Minimum Stein Discrepancy Estimators Alessandro Barp François‐Xavier Briol Andrew B. Duncan Mark Girolami Lester W. Mackey 80 93 0 19 Jun 2019
Kernelized Complete Conditional Stein Discrepancy Raghav Singhal Xintian Han S. Lahlou Rajesh Ranganath 87 7 0 09 Apr 2019
Generalized Variational Inference: Three arguments for deriving new Posteriors Jeremias Knoblauch Jack Jewson Theodoros Damoulas DRL BDL 109 106 0 03 Apr 2019
Gaussian Mean Field Regularizes by Limiting Learned Information Julius Kunze Louis Kirsch H. Ritter David Barber FedML MLT 49 2 0 12 Feb 2019
GO Gradient for Expectation-Based Objectives Yulai Cong Miaoyun Zhao Ke Bai Lawrence Carin 150 16 0 17 Jan 2019
Posterior inference unchained with EL_2O U. Seljak Byeonghee Yu 49 10 0 14 Jan 2019
Simple, Distributed, and Accelerated Probabilistic Programming Like Hui Matthew Hoffman Siyuan Ma Christopher Suter Srinivas Vasudevan Alexey Radul M. Belkin Rif A. Saurous BDL 85 56 0 05 Nov 2018
Doubly Semi-Implicit Variational Inference Dmitry Molchanov V. Kharitonov Artem Sobolev Dmitry Vetrov BDL 87 40 0 05 Oct 2018
A Spectral Approach to Gradient Estimation for Implicit Distributions Jiaxin Shi Shengyang Sun Jun Zhu 87 92 0 07 Jun 2018
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with $β$ -Divergences Jeremias Knoblauch Jack Jewson Theodoros Damoulas 78 58 0 06 Jun 2018
Wasserstein Variational Inference L. Ambrogioni Umut Güçlü Yağmur Güçlütürk Max Hinne E. Maris Marcel van Gerven BDL DRL 111 42 0 29 May 2018
A particle-based variational approach to Bayesian Non-negative Matrix Factorization M. A. Masood Finale Doshi-Velez 63 11 0 16 Mar 2018
Learning Latent Permutations with Gumbel-Sinkhorn Networks Gonzalo E. Mena David Belanger Scott W. Linderman Jasper Snoek 120 272 0 23 Feb 2018
Variational Inference over Non-differentiable Cardiac Simulators using Bayesian Optimization Adam McCarthy Blanca Rodriguez A. Mincholé 155 5 0 09 Dec 2017
Stochastic Maximum Likelihood Optimization via Hypernetworks Abdul-Saboor Sheikh Kashif Rasul A. Merentitis Urs M. Bergmann 109 18 0 04 Dec 2017
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 233 698 0 15 Nov 2017
Fixing a Broken ELBO Alexander A. Alemi Ben Poole Ian S. Fischer Joshua V. Dillon Rif A. Saurous Kevin Patrick Murphy DRL BDL 101 80 0 01 Nov 2017
Continuous-Time Flows for Efficient Inference and Density Estimation Changyou Chen Chunyuan Li Liquan Chen Wenlin Wang Yunchen Pu Lawrence Carin TPM 129 57 0 04 Sep 2017
Learning Model Reparametrizations: Implicit Variational Inference by Fitting MCMC distributions Michalis K. Titsias BDL 72 23 0 04 Aug 2017
Adversarial Variational Optimization of Non-Differentiable Simulators Gilles Louppe Joeri Hermans Kyle Cranmer GAN 173 66 0 22 Jul 2017
Learning to Draw Samples with Amortized Stein Variational Gradient Descent Yihao Feng Dilin Wang Qiang Liu GAN BDL 85 82 0 20 Jul 2017