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Variational Inference with Normalizing Flows

21 May 2015

Danilo Jimenez Rezende

Papers citing "Variational Inference with Normalizing Flows"

50 / 2,268 papers shown

Title
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 212 198 0 13 Feb 2018
Black-box Variational Inference for Stochastic Differential Equations Tom Ryder Andrew Golightly A. Mcgough D. Prangle 91 58 0 09 Feb 2018
Neural Network Renormalization Group Shuo-Hui Li Lei Wang BDL DRL 112 125 0 08 Feb 2018
Semi-Amortized Variational Autoencoders Yoon Kim Sam Wiseman Andrew C. Miller David Sontag Alexander M. Rush BDL DRL 172 243 0 07 Feb 2018
Improving Variational Encoder-Decoders in Dialogue Generation Xiaoyu Shen Hui Su Shuzi Niu Vera Demberg DRL 92 99 0 06 Feb 2018
Inference Suboptimality in Variational Autoencoders Chris Cremer Xuechen Li David Duvenaud DRL BDL 137 283 0 10 Jan 2018
Generating Neural Networks with Neural Networks Lior Deutsch 105 21 0 06 Jan 2018
PixelSNAIL: An Improved Autoregressive Generative Model Xi Chen Nikhil Mishra Mostafa Rohaninejad Pieter Abbeel DRL DiffM BDL GAN 80 276 0 28 Dec 2017
Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators Mario Lezcano Casado A. G. Baydin David Martínez-Rubio T. Le Frank Wood ... Gilles Louppe Kyle Cranmer Karen Ng W. Bhimji P. Prabhat 166 9 0 21 Dec 2017
Deep generative models of genetic variation capture mutation effects Adam J. Riesselman John Ingraham D. Marks DRL BDL 50 23 0 18 Dec 2017
GibbsNet: Iterative Adversarial Inference for Deep Graphical Models Alex Lamb R. Devon Hjelm Yaroslav Ganin Joseph Paul Cohen Aaron Courville Yoshua Bengio GAN 72 13 0 12 Dec 2017
Noisy Natural Gradient as Variational Inference Guodong Zhang Shengyang Sun David Duvenaud Roger C. Grosse ODL 102 212 0 06 Dec 2017
Stochastic Maximum Likelihood Optimization via Hypernetworks Abdul-Saboor Sheikh Kashif Rasul A. Merentitis Urs M. Bergmann 109 18 0 04 Dec 2017
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 134 47 0 01 Dec 2017
Riemannian Stein Variational Gradient Descent for Bayesian Inference Chang-rui Liu Jun Zhu 65 67 0 30 Nov 2017
Parallel WaveNet: Fast High-Fidelity Speech Synthesis Aaron van den Oord Yazhe Li Igor Babuschkin Karen Simonyan Oriol Vinyals ... Alex Graves Helen King T. Walters Dan Belov Demis Hassabis 233 859 0 28 Nov 2017
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 236 698 0 15 Nov 2017
Variational Adaptive-Newton Method for Explorative Learning Mohammad Emtiyaz Khan Wu Lin Voot Tangkaratt Zuozhu Liu Didrik Nielsen ODL 89 20 0 15 Nov 2017
Z-Forcing: Training Stochastic Recurrent Networks Anirudh Goyal Alessandro Sordoni Marc-Alexandre Côté Nan Rosemary Ke Yoshua Bengio BDL 93 186 0 15 Nov 2017
Adversarial Symmetric Variational Autoencoder Yunchen Pu Weiyao Wang Ricardo Henao Liqun Chen Zhe Gan Chunyuan Li Lawrence Carin DRL GAN 97 78 0 14 Nov 2017
Neural Variational Inference and Learning in Undirected Graphical Models Volodymyr Kuleshov Stefano Ermon BDL 69 34 0 07 Nov 2017
Neural Discrete Representation Learning Aaron van den Oord Oriol Vinyals Koray Kavukcuoglu BDL SSL OCL 257 5,093 0 02 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
Latent Space Oddity: on the Curvature of Deep Generative Models Georgios Arvanitidis Lars Kai Hansen Søren Hauberg DRL 135 271 0 31 Oct 2017
On the challenges of learning with inference networks on sparse, high-dimensional data Rahul G. Krishnan Dawen Liang Matthew Hoffman CML BDL 87 85 0 17 Oct 2017
Unsupervised Real-Time Control through Variational Empowerment Maximilian Karl Maximilian Soelch Philip Becker-Ehmck Djalel Benbouzid Patrick van der Smagt Justin Bayer 78 55 0 13 Oct 2017
Bayesian Hypernetworks David M. Krueger Chin-Wei Huang Riashat Islam Ryan Turner Alexandre Lacoste Aaron Courville UQCV BDL 82 139 0 13 Oct 2017
Learnable Explicit Density for Continuous Latent Space and Variational Inference Chin-Wei Huang Ahmed Touati Laurent Dinh M. Drozdzal Mohammad Havaei Laurent Charlin Aaron Courville BDL DRL 94 28 0 06 Oct 2017
Variational Memory Addressing in Generative Models J. Bornschein A. Mnih Daniel Zoran Danilo Jimenez Rezende BDL 89 63 0 21 Sep 2017
ZhuSuan: A Library for Bayesian Deep Learning Jiaxin Shi Jianfei Chen Jun Zhu Shengyang Sun Yucen Luo Yihong Gu Yuhao Zhou UQCV BDL 82 43 0 18 Sep 2017
Disentangled Variational Auto-Encoder for Semi-supervised Learning Yang Li Quan Pan Suhang Wang Haiyun Peng Tao Yang Min Zhang DRL 69 88 0 15 Sep 2017
Symmetric Variational Autoencoder and Connections to Adversarial Learning Liqun Chen Shuyang Dai Yunchen Pu Chunyuan Li Weiyao Wang Lawrence Carin DRL GAN 109 71 0 06 Sep 2017
Unsupervised Generative Modeling Using Matrix Product States Zhaoyu Han Jun Wang H. Fan Lei Wang Pan Zhang 144 273 0 06 Sep 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 80 23 0 04 Aug 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
A causal framework for explaining the predictions of black-box sequence-to-sequence models David Alvarez-Melis Tommi Jaakkola CML 368 206 0 06 Jul 2017
Bayesian Semisupervised Learning with Deep Generative Models Jonathan Gordon José Miguel Hernández-Lobato BDL UQCV GAN 75 27 0 29 Jun 2017
Dr.VAE: Drug Response Variational Autoencoder Ladislav Rampášek Daniel Hidru P. Smirnov B. Haibe-Kains Anna Goldenberg DRL 54 32 0 26 Jun 2017
A-NICE-MC: Adversarial Training for MCMC Jiaming Song Shengjia Zhao Stefano Ermon BDL OOD 127 110 0 23 Jun 2017
A Divergence Bound for Hybrids of MCMC and Variational Inference and an Application to Langevin Dynamics and SGVI Justin Domke BDL 80 6 0 20 Jun 2017
Adversarially Regularized Autoencoders Jiaqi Zhao Yoon Kim Kelly Zhang Alexander M. Rush Yann LeCun DRL GNN GAN 75 78 0 13 Jun 2017
Channel-Recurrent Autoencoding for Image Modeling Wenling Shang Kihyuk Sohn Yuandong Tian DRL GAN 27 3 0 12 Jun 2017
Tackling Over-pruning in Variational Autoencoders Serena Yeung A. Kannan Yann N. Dauphin Li Fei-Fei DRL 179 63 0 09 Jun 2017
Improving Variational Auto-Encoders using convex combination linear Inverse Autoregressive Flow Jakub M. Tomczak Max Welling DRL 85 24 0 07 Jun 2017
DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data Swaminathan Gurumurthy Ravi Kiran Sarvadevabhatla R. Venkatesh Babu GAN 101 272 0 07 Jun 2017
Variational Sequential Monte Carlo C. A. Naesseth Scott W. Linderman Rajesh Ranganath David M. Blei BDL 307 215 0 31 May 2017
Surface Networks Ilya Kostrikov Zhongshi Jiang Daniele Panozzo Denis Zorin Joan Bruna 89 101 0 30 May 2017
Kernel Implicit Variational Inference Jiaxin Shi Shengyang Sun Jun Zhu BDL 96 3 0 29 May 2017
Filtering Variational Objectives Chris J. Maddison Dieterich Lawson George Tucker N. Heess Mohammad Norouzi A. Mnih Arnaud Doucet Yee Whye Teh FedML 262 210 0 25 May 2017