Importance Weighted Autoencoders

1 September 2015

Papers citing "Importance Weighted Autoencoders"

50 / 793 papers shown

Title
ZhuSuan: A Library for Bayesian Deep Learning Jiaxin Shi Jianfei Chen Jun Zhu Shengyang Sun Yucen Luo Yihong Gu Yuhao Zhou UQCV BDL 38 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 21 86 0 15 Sep 2017
Meta-Learning MCMC Proposals Tongzhou Wang Yi Wu David A. Moore Stuart J. Russell BDL 26 2 0 21 Aug 2017
Energy-based Models for Video Anomaly Detection H. Vu Dinh Q. Phung T. Nguyen Anthony Trevors Svetha Venkatesh 26 22 0 17 Aug 2017
Learning to Draw Samples with Amortized Stein Variational Gradient Descent Yihao Feng Dilin Wang Qiang Liu GAN BDL 34 79 0 20 Jul 2017
Guiding InfoGAN with Semi-Supervision Adrian Spurr Emre Aksan Otmar Hilliges GAN 34 46 0 14 Jul 2017
Bayesian Semisupervised Learning with Deep Generative Models Jonathan Gordon José Miguel Hernández-Lobato BDL UQCV GAN 32 27 0 29 Jun 2017
An online sequence-to-sequence model for noisy speech recognition Chung-Cheng Chiu Dieterich Lawson Yuping Luo George Tucker Kevin Swersky Ilya Sutskever Navdeep Jaitly 19 7 0 16 Jun 2017
Channel-Recurrent Autoencoding for Image Modeling Wenling Shang Kihyuk Sohn Yuandong Tian DRL GAN 16 3 0 12 Jun 2017
Tackling Over-pruning in Variational Autoencoders Serena Yeung A. Kannan Yann N. Dauphin Li Fei-Fei DRL 22 63 0 09 Jun 2017
Sliced Wasserstein Generative Models Jiqing Wu Zhiwu Huang Dinesh Acharya Wen Li Janine Thoma Danda Pani Paudel Luc Van Gool DiffM 22 0 0 08 Jun 2017
InfoVAE: Information Maximizing Variational Autoencoders Shengjia Zhao Jiaming Song Stefano Ermon DRL 49 440 0 07 Jun 2017
DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data Swaminathan Gurumurthy Ravi Kiran Sarvadevabhatla R. Venkatesh Babu GAN 30 270 0 07 Jun 2017
On Unifying Deep Generative Models Zhiting Hu Zichao Yang Ruslan Salakhutdinov Eric Xing DRL GAN 41 127 0 02 Jun 2017
Learning Disentangled Representations with Semi-Supervised Deep Generative Models Siddharth Narayanaswamy Brooks Paige Jan-Willem van de Meent Alban Desmaison Noah D. Goodman Pushmeet Kohli Frank Wood Philip Torr DRL CoGe 36 359 0 01 Jun 2017
Variational Sequential Monte Carlo C. A. Naesseth Scott W. Linderman Rajesh Ranganath David M. Blei BDL 27 214 0 31 May 2017
Auto-Encoding Sequential Monte Carlo T. Le Maximilian Igl Tom Rainforth Tom Jin Frank Wood BDL DRL 24 151 0 29 May 2017
Lifelong Generative Modeling Jason Ramapuram Magda Gregorova Alexandros Kalousis BDL CLL 24 119 0 27 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
VAE with a VampPrior Jakub M. Tomczak Max Welling GAN BDL 36 622 0 19 May 2017
Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions Zhengyang Wang Hao Yuan Shuiwang Ji DRL 34 8 0 18 May 2017
Learning Hard Alignments with Variational Inference Dieterich Lawson Chung-Cheng Chiu George Tucker Colin Raffel Kevin Swersky Navdeep Jaitly DRL 15 29 0 16 May 2017
Learning Multimodal Transition Dynamics for Model-Based Reinforcement Learning Thomas M. Moerland Joost Broekens Catholijn M. Jonker OffRL 22 31 0 01 May 2017
Semi-supervised Bayesian Deep Multi-modal Emotion Recognition Changde Du Changying Du Jinpeng Li Wei-Long Zheng Bao-Liang Lu Huiguang He 11 9 0 25 Apr 2017
VAE Learning via Stein Variational Gradient Descent Yunchen Pu Zhe Gan Ricardo Henao Chunyuan Li Shaobo Han Lawrence Carin DRL 23 6 0 18 Apr 2017
Creativity: Generating Diverse Questions using Variational Autoencoders Unnat Jain Ziyu Zhang Alex Schwing 25 152 0 11 Apr 2017
Continuously tempered Hamiltonian Monte Carlo Matthew M. Graham Amos J. Storkey 27 26 0 11 Apr 2017
Reinterpreting Importance-Weighted Autoencoders Chris Cremer Q. Morris David Duvenaud BDL FAtt 11 94 0 10 Apr 2017
Learning Approximately Objective Priors Eric T. Nalisnick Padhraic Smyth 18 11 0 04 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
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models George Tucker A. Mnih Chris J. Maddison John Lawson Jascha Narain Sohl-Dickstein BDL 47 282 0 21 Mar 2017
Particle Value Functions Chris J. Maddison Dieterich Lawson George Tucker N. Heess Arnaud Doucet A. Mnih Yee Whye Teh 14 15 0 16 Mar 2017
Towards Deeper Understanding of Variational Autoencoding Models Shengjia Zhao Jiaming Song Stefano Ermon DRL 33 155 0 28 Feb 2017
Approximate Inference with Amortised MCMC Yingzhen Li Richard Turner Qiang Liu BDL 22 61 0 27 Feb 2017
Coarse Grained Exponential Variational Autoencoders Ke Sun Xiangliang Zhang DRL BDL 16 0 0 25 Feb 2017
On the Origin of Deep Learning Haohan Wang Bhiksha Raj MedIm 3DV VLM 48 223 0 24 Feb 2017
A Deep Convolutional Auto-Encoder with Pooling - Unpooling Layers in Caffe V. Turchenko Eric Chalmers Artur Luczak SSL 13 74 0 18 Jan 2017
Image Generation and Editing with Variational Info Generative AdversarialNetworks Mahesh Gorijala Ambedkar Dukkipati GAN 21 15 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
An Architecture for Deep, Hierarchical Generative Models Philip Bachman AI4CE BDL 33 53 0 08 Dec 2016
Fast Adaptation in Generative Models with Generative Matching Networks Sergey Bartunov Dmitry P. Vetrov GAN 21 23 0 07 Dec 2016
Piecewise Latent Variables for Neural Variational Text Processing Iulian Serban Alexander Ororbia Joelle Pineau Aaron Courville DRL BDL 24 2 0 01 Dec 2016
Improving Variational Auto-Encoders using Householder Flow Jakub M. Tomczak Max Welling BDL DRL 37 173 0 29 Nov 2016
Robust Variational Inference Michael Figurnov Kirill Struminsky Dmitry Vetrov BDL DRL AAML 26 1 0 28 Nov 2016
Bottleneck Conditional Density Estimation Rui Shu Hung Bui Mohammad Ghavamzadeh BDL 16 23 0 25 Nov 2016
Adaptive Feature Abstraction for Translating Video to Text Yunchen Pu Martin Renqiang Min Zhe Gan Lawrence Carin 41 14 0 23 Nov 2016
Max-Margin Deep Generative Models for (Semi-)Supervised Learning Chongxuan Li Jun Zhu Bo Zhang AI4CE 32 42 0 22 Nov 2016
Deep Variational Inference Without Pixel-Wise Reconstruction Siddharth Agrawal Ambedkar Dukkipati DRL 3DV BDL 30 13 0 16 Nov 2016