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Variational Inference with Normalizing Flows

21 May 2015

Danilo Jimenez Rezende

Papers citing "Variational Inference with Normalizing Flows"

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Title
Discrete Flows: Invertible Generative Models of Discrete Data Dustin Tran Keyon Vafa Kumar Krishna Agrawal Laurent Dinh Ben Poole DRL 164 117 0 24 May 2019
Variational Inference with Mixture Model Approximation: Robotic Applications Emmanuel Pignat Teguh Santoso Lembono Sylvain Calinon 31 2 0 23 May 2019
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures Xiaoting Shao Alejandro Molina Antonio Vergari Karl Stelzner Robert Peharz Thomas Liebig Kristian Kersting BDL TPM 82 35 0 21 May 2019
Non-Autoregressive Neural Text-to-Speech Kainan Peng Ming-Yu Liu Z. Song Kexin Zhao 101 40 0 21 May 2019
Minimal Achievable Sufficient Statistic Learning Milan Cvitkovic Günther Koliander 84 12 0 19 May 2019
Automatic Posterior Transformation for Likelihood-Free Inference David S. Greenberg M. Nonnenmacher Jakob H. Macke 414 332 0 17 May 2019
Integer Discrete Flows and Lossless Compression Emiel Hoogeboom Jorn W. T. Peters Rianne van den Berg Max Welling 165 160 0 17 May 2019
Leveraging exploration in off-policy algorithms via normalizing flows Bogdan Mazoure T. Doan A. Durand R. Devon Hjelm Joelle Pineau OnRL 68 62 0 16 May 2019
The Incomplete Rosetta Stone Problem: Identifiability Results for Multi-View Nonlinear ICA Luigi Gresele Paul Kishan Rubenstein Arash Mehrjou Francesco Locatello Bernhard Schölkopf 57 100 0 16 May 2019
Correlated Variational Auto-Encoders Da Tang Dawen Liang Tony Jebara Nicholas Ruozzi CML GNN 69 21 0 14 May 2019
Learning Hierarchical Priors in VAEs Alexej Klushyn Nutan Chen Richard Kurle Botond Cseke Patrick van der Smagt BDL CML DRL 105 101 0 13 May 2019
Importance Weighted Hierarchical Variational Inference Artem Sobolev Dmitry Vetrov BDL 79 29 0 08 May 2019
A Generative Model for Sampling High-Performance and Diverse Weights for Neural Networks Lior Deutsch Erik Nijkamp Yu Yang 71 16 0 07 May 2019
Sum-of-Squares Polynomial Flow P. Jaini Kira A. Selby Yaoliang Yu TPM 103 143 0 07 May 2019
Semi-Conditional Normalizing Flows for Semi-Supervised Learning Andrei Atanov Alexandra Volokhova Arsenii Ashukha Ivan Sosnovik Dmitry Vetrov BDL 96 42 0 01 May 2019
Neural source-filter waveform models for statistical parametric speech synthesis Xin Wang Shinji Takaki Junichi Yamagishi 97 118 0 27 Apr 2019
Exponential Family Estimation via Adversarial Dynamics Embedding Bo Dai Ziqiang Liu H. Dai Niao He Arthur Gretton Le Song Dale Schuurmans 82 53 0 27 Apr 2019
Conditionally structured variational Gaussian approximation with importance weights Linda S. L. Tan Aishwarya Bhaskaran David J. Nott 125 13 0 21 Apr 2019
Effective Estimation of Deep Generative Language Models Tom Pelsmaeker Wilker Aziz BDL 92 28 0 17 Apr 2019
High-dimensional copula variational approximation through transformation M. Smith Rubén Loaiza-Maya David J. Nott 79 33 0 16 Apr 2019
Learning Probabilistic Multi-Modal Actor Models for Vision-Based Robotic Grasping Mengyuan Yan A. Li Mrinal Kalakrishnan P. Pastor 57 18 0 15 Apr 2019
Exact Rate-Distortion in Autoencoders via Echo Noise Rob Brekelmans Daniel Moyer Aram Galstyan Greg Ver Steeg 59 17 0 15 Apr 2019
Three scenarios for continual learning Gido M. van de Ven A. Tolias CLL 104 897 0 15 Apr 2019
Generative Hybrid Representations for Activity Forecasting with No-Regret Learning Jiaqi Guan Ye Yuan Kris Kitani Nicholas Rhinehart AI4TS 74 31 0 12 Apr 2019
Block Neural Autoregressive Flow Nicola De Cao Ivan Titov Wilker Aziz DRL 86 125 0 09 Apr 2019
Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling P. Wang William Yang Wang DRL 97 27 0 04 Apr 2019
Density Matching for Bilingual Word Embedding Chunting Zhou Xuezhe Ma Di Wang Graham Neubig 99 40 0 04 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
Nonparametric Density Estimation for High-Dimensional Data - Algorithms and Applications Zhipeng Wang D. W. Scott 85 71 0 30 Mar 2019
Wasserstein Dependency Measure for Representation Learning Sherjil Ozair Corey Lynch Yoshua Bengio Aaron van den Oord Sergey Levine P. Sermanet SSL DRL 146 119 0 28 Mar 2019
Approximating exponential family models (not single distributions) with a two-network architecture Sean R. Bittner John P. Cunningham 46 4 0 18 Mar 2019
Topic-Guided Variational Autoencoders for Text Generation Wenlin Wang Zhe Gan Hongteng Xu Ruiyi Zhang Guoyin Wang Dinghan Shen Changyou Chen Lawrence Carin BDL 90 127 0 17 Mar 2019
MSG-GAN: Multi-Scale Gradients for Generative Adversarial Networks Animesh Karnewar Oliver Wang GAN 85 50 0 14 Mar 2019
Diagnosing and Enhancing VAE Models Bin Dai David Wipf DRL 101 381 0 14 Mar 2019
Variational Bayesian Optimal Experimental Design Adam Foster M. Jankowiak Eli Bingham Paul Horsfall Yee Whye Teh Tom Rainforth Noah D. Goodman 99 140 0 13 Mar 2019
Semantics Preserving Adversarial Learning Ousmane Amadou Dia Elnaz Barshan Reza Babanezhad AAML GAN 113 2 0 10 Mar 2019
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport Matthew Hoffman Pavel Sountsov Joshua V. Dillon I. Langmore Dustin Tran Srinivas Vasudevan BDL 76 108 0 09 Mar 2019
A Deep Generative Model of Speech Complex Spectrograms Aditya Arie Nugraha Kouhei Sekiguchi Kazuyoshi Yoshii 47 19 0 08 Mar 2019
VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation Manoj Kumar Mohammad Babaeizadeh D. Erhan Chelsea Finn Sergey Levine Laurent Dinh Durk Kingma VGen 98 132 0 04 Mar 2019
Conditional Density Estimation with Neural Networks: Best Practices and Benchmarks Jonas Rothfuss Fabio Ferreira Simon Walther Maxim Ulrich TPM 124 75 0 03 Mar 2019
Adversarially Approximated Autoencoder for Image Generation and Manipulation Wenju Xu Shawn Keshmiri Guanghui Wang GAN 96 72 0 14 Feb 2019
Unpriortized Autoencoder For Image Generation Jaeyoung Yoo Hojun Lee Nojun Kwak SyDa SSL GAN DRL 34 2 0 12 Feb 2019
A stochastic version of Stein Variational Gradient Descent for efficient sampling Lei Li Yingzhou Li Jian‐Guo Liu Zibu Liu Jianfeng Lu 63 35 0 09 Feb 2019
Hybrid Models with Deep and Invertible Features Eric T. Nalisnick Akihiro Matsukawa Yee Whye Teh Dilan Görür Balaji Lakshminarayanan BDL DRL 119 99 0 07 Feb 2019
Reversible GANs for Memory-efficient Image-to-Image Translation Tycho F. A. van der Ouderaa Daniel E. Worrall 64 55 0 07 Feb 2019
BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling Lars Maaløe Marco Fraccaro Valentin Liévin Ole Winther BDL DRL 93 215 0 06 Feb 2019
Predictive Uncertainty Quantification with Compound Density Networks Agustinus Kristiadi Sina Daubener Asja Fischer BDL UQCV 83 17 0 04 Feb 2019
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design Jonathan Ho Xi Chen A. Srinivas Yan Duan Pieter Abbeel DRL 105 451 0 01 Feb 2019
Emerging Convolutions for Generative Normalizing Flows Emiel Hoogeboom Rianne van den Berg Max Welling DRL 135 98 0 30 Jan 2019
Deep Archetypal Analysis S. Keller M. Samarin Mario Wieser Volker Roth 65 18 0 30 Jan 2019