Variational Inference with Normalizing Flows

21 May 2015

Danilo Jimenez Rezende

Papers citing "Variational Inference with Normalizing Flows"

47 / 847 papers shown

Title
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 33 28 0 06 Oct 2017
Disentangled Variational Auto-Encoder for Semi-supervised Learning Yang Li Quan Pan Suhang Wang Haiyun Peng Tao Yang Min Zhang DRL 21 86 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 38 70 0 06 Sep 2017
Unsupervised Generative Modeling Using Matrix Product States Zhaoyu Han Jun Wang H. Fan Lei Wang Pan Zhang 24 268 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 46 57 0 04 Sep 2017
Bayesian Semisupervised Learning with Deep Generative Models Jonathan Gordon José Miguel Hernández-Lobato BDL UQCV GAN 32 27 0 29 Jun 2017
Kernel Implicit Variational Inference Jiaxin Shi Shengyang Sun Jun Zhu BDL 29 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 22 210 0 25 May 2017
Proximity Variational Inference Jaan Altosaar Rajesh Ranganath David M. Blei BDL 8 21 0 24 May 2017
Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models Aditya Grover Manik Dhar Stefano Ermon GAN 39 24 0 24 May 2017
Causal Effect Inference with Deep Latent-Variable Models Christos Louizos Uri Shalit Joris Mooij David Sontag R. Zemel Max Welling CML BDL 69 728 0 24 May 2017
Reducing Reparameterization Gradient Variance Andrew C. Miller N. Foti Alexander DÁmour Ryan P. Adams 27 84 0 22 May 2017
Gradient Estimators for Implicit Models Yingzhen Li Richard Turner 35 104 0 19 May 2017
Stein Variational Adaptive Importance Sampling J. Han Qiang Liu 24 28 0 18 Apr 2017
Reinterpreting Importance-Weighted Autoencoders Chris Cremer Q. Morris David Duvenaud BDL FAtt 11 94 0 10 Apr 2017
Semi-Supervised Generation with Cluster-aware Generative Models Lars Maaløe Marco Fraccaro Ole Winther 23 28 0 03 Apr 2017
Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference Geoffrey Roeder Yuhuai Wu David Duvenaud BDL 25 196 0 27 Mar 2017
Inference via low-dimensional couplings Alessio Spantini Daniele Bigoni Youssef Marzouk 40 119 0 17 Mar 2017
Sharp Minima Can Generalize For Deep Nets Laurent Dinh Razvan Pascanu Samy Bengio Yoshua Bengio ODL 46 757 0 15 Mar 2017
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks Christos Louizos Max Welling BDL 21 454 0 06 Mar 2017
Hierarchical Implicit Models and Likelihood-Free Variational Inference Dustin Tran Rajesh Ranganath David M. Blei VLM GAN 30 100 0 28 Feb 2017
Improved Variational Autoencoders for Text Modeling using Dilated Convolutions Zichao Yang Zhiting Hu Ruslan Salakhutdinov Taylor Berg-Kirkpatrick 24 383 0 27 Feb 2017
Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks L. Mescheder Sebastian Nowozin Andreas Geiger GAN BDL 49 525 0 17 Jan 2017
Deep Probabilistic Programming Dustin Tran Matthew D. Hoffman Rif A. Saurous E. Brevdo Kevin Patrick Murphy David M. Blei BDL 36 193 0 13 Jan 2017
Two Methods For Wild Variational Inference Qiang Liu Yihao Feng BDL 32 19 0 30 Nov 2016
Deep Variational Inference Without Pixel-Wise Reconstruction Siddharth Agrawal Ambedkar Dukkipati DRL 3DV BDL 30 13 0 16 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 47 671 0 08 Nov 2016
Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning Dilin Wang Qiang Liu GAN BDL 38 118 0 06 Nov 2016
Structured Inference Networks for Nonlinear State Space Models Rahul G. Krishnan Uri Shalit David Sontag BDL 16 452 0 30 Sep 2016
Variational Inference with Hamiltonian Monte Carlo Christopher Wolf Maximilian Karl Patrick van der Smagt BDL 23 37 0 26 Sep 2016
Discrete Variational Autoencoders J. Rolfe BDL DRL 35 254 0 07 Sep 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm Qiang Liu Dilin Wang BDL 19 1,069 0 16 Aug 2016
Improving Variational Inference with Inverse Autoregressive Flow Diederik P. Kingma Tim Salimans Rafal Jozefowicz Xi Chen Ilya Sutskever Max Welling BDL DRL 55 1,797 0 15 Jun 2016
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 97 3,647 0 26 May 2016
Gaussian variational approximation with sparse precision matrices Linda S. L. Tan David J. Nott 30 76 0 18 May 2016
One-Shot Generalization in Deep Generative Models Danilo Jimenez Rezende S. Mohamed Ivo Danihelka Karol Gregor Daan Wierstra BDL VLM DRL LRM 30 254 0 16 Mar 2016
Automatic Differentiation Variational Inference A. Kucukelbir Dustin Tran Rajesh Ranganath Andrew Gelman David M. Blei 38 709 0 02 Mar 2016
Variational inference for Monte Carlo objectives A. Mnih Danilo Jimenez Rezende DRL BDL 52 288 0 22 Feb 2016
Black box variational inference for state space models Evan Archer Il Memming Park Lars Buesing John P. Cunningham Liam Paninski BDL 26 160 0 23 Nov 2015
The Variational Gaussian Process Dustin Tran Rajesh Ranganath David M. Blei BDL 29 184 0 20 Nov 2015
Generating Sentences from a Continuous Space Samuel R. Bowman Luke Vilnis Oriol Vinyals Andrew M. Dai Rafal Jozefowicz Samy Bengio DRL 34 2,341 0 19 Nov 2015
Super-Resolution with Deep Convolutional Sufficient Statistics Joan Bruna Pablo Sprechmann Yann LeCun SupR 25 323 0 18 Nov 2015
Deep Kalman Filters Rahul G. Krishnan Uri Shalit David Sontag BDL AI4TS 19 370 0 16 Nov 2015
Hierarchical Variational Models Rajesh Ranganath Dustin Tran David M. Blei DRL VLM 23 335 0 07 Nov 2015
Stochastic gradient descent methods for estimation with large data sets Dustin Tran Panos Toulis E. Airoldi 12 14 0 22 Sep 2015
Importance Weighted Autoencoders Yuri Burda Roger C. Grosse Ruslan Salakhutdinov BDL 13 1,236 0 01 Sep 2015
Data Generation as Sequential Decision Making Philip Bachman Doina Precup 22 57 0 10 Jun 2015