Variational inference for Monte Carlo objectives

22 February 2016

A. Mnih

Danilo Jimenez Rezende

DRL

BDL

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Papers citing "Variational inference for Monte Carlo objectives"

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Title
SCALOR: Generative World Models with Scalable Object Representations Jindong Jiang Sepehr Janghorbani Gerard de Melo Sungjin Ahn OCL DRL 37 132 0 06 Oct 2019
Select and Attend: Towards Controllable Content Selection in Text Generation Xiaoyu Shen Jun Suzuki Kentaro Inui Hui Su Dietrich Klakow Satoshi Sekine 24 28 0 10 Sep 2019
Probabilistic Models with Deep Neural Networks A. Masegosa Rafael Cabañas H. Langseth Thomas D. Nielsen Antonio Salmerón BDL 6 12 0 09 Aug 2019
Cooperative image captioning Gilad Vered Gal Oren Y. Atzmon Gal Chechik 26 2 0 26 Jul 2019
A Tandem Learning Rule for Effective Training and Rapid Inference of Deep Spiking Neural Networks Jibin Wu Yansong Chua Malu Zhang Guoqi Li Haizhou Li Kay Chen Tan 21 14 0 02 Jul 2019
The Thermodynamic Variational Objective Vaden Masrani T. Le Frank D. Wood 14 48 0 28 Jun 2019
Teaching deep neural networks to localize single molecules for super-resolution microscopy Artur Speiser Lucas-Raphael Müller Ulf Matti Christopher J. Obara Wesley R. Legant Jonas Ries Jakob H. Macke Srinivas C. Turaga 11 17 0 27 Jun 2019
Amortized Bethe Free Energy Minimization for Learning MRFs Sam Wiseman Yoon Kim TPM DRL 11 11 0 14 Jun 2019
Learning Deep Generative Models with Annealed Importance Sampling Xinqiang Ding David J. Freedman VLM BDL GAN 26 10 0 12 Jun 2019
Importance Weighted Adversarial Variational Autoencoders for Spike Inference from Calcium Imaging Data Daniel Jiwoong Im Sridhama Prakhya Jinyao Yan Srinivas C. Turaga K. Branson BDL 11 2 0 07 Jun 2019
An Introduction to Variational Autoencoders Diederik P. Kingma Max Welling BDL SSL DRL 33 2,288 0 06 Jun 2019
Learning Discrete and Continuous Factors of Data via Alternating Disentanglement Yeonwoo Jeong Hyun Oh Song 13 48 0 23 May 2019
Unsupervised Linear and Nonlinear Channel Equalization and Decoding using Variational Autoencoders Avi Caciularu D. Burshtein 12 48 0 21 May 2019
Optimizing Sequential Medical Treatments with Auto-Encoding Heuristic Search in POMDPs Luchen Li Matthieu Komorowski Aldo A. Faisal OffRL 18 13 0 17 May 2019
Hierarchical Importance Weighted Autoencoders Chin-Wei Huang Kris Sankaran Eeshan Gunesh Dhekane Alexandre Lacoste Aaron Courville BDL 11 15 0 13 May 2019
ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables Mingzhang Yin Yuguang Yue Mingyuan Zhou 14 23 0 04 May 2019
Unsupervised Recurrent Neural Network Grammars Yoon Kim Alexander M. Rush Lei Yu A. Kuncoro Chris Dyer Gábor Melis LRM RALM SSL 20 115 0 07 Apr 2019
Imitation Learning of Factored Multi-agent Reactive Models Michael Teng T. Le Adam Scibior Frank D. Wood DRL 12 1 0 12 Mar 2019
Total stochastic gradient algorithms and applications in reinforcement learning Paavo Parmas 20 17 0 05 Feb 2019
PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos Paavo Parmas C. Rasmussen Jan Peters Kenji Doya 8 85 0 04 Feb 2019
GO Gradient for Expectation-Based Objectives Yulai Cong Miaoyun Zhao Ke Bai Lawrence Carin 18 16 0 17 Jan 2019
Undirected Graphical Models as Approximate Posteriors Arash Vahdat Evgeny Andriyash W. Macready 14 2 0 11 Jan 2019
Credit Assignment Techniques in Stochastic Computation Graphs T. Weber N. Heess Lars Buesing David Silver 13 45 0 07 Jan 2019
A Tutorial on Deep Latent Variable Models of Natural Language Yoon Kim Sam Wiseman Alexander M. Rush BDL VLM 27 42 0 17 Dec 2018
Recent Advances in Autoencoder-Based Representation Learning Michael Tschannen Olivier Bachem Mario Lucic OOD SSL DRL 12 440 0 12 Dec 2018
Neural Joint Source-Channel Coding Kristy Choi Kedar Tatwawadi Aditya Grover Tsachy Weissman Stefano Ermon 11 38 0 19 Nov 2018
Neural Nearest Neighbors Networks Tobias Plötz Stefan Roth 19 338 0 30 Oct 2018
Rao-Blackwellized Stochastic Gradients for Discrete Distributions Runjing Liu Jeffrey Regier Nilesh Tripuraneni Michael I. Jordan Jon D. McAuliffe 15 31 0 10 Oct 2018
Feature Selection using Stochastic Gates Yutaro Yamada Ofir Lindenbaum S. Negahban Y. Kluger 22 43 0 09 Oct 2018
Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives George Tucker Dieterich Lawson S. Gu Chris J. Maddison BDL 19 110 0 09 Oct 2018
Improved Gradient-Based Optimization Over Discrete Distributions Evgeny Andriyash Arash Vahdat W. Macready 16 9 0 29 Sep 2018
InfoSSM: Interpretable Unsupervised Learning of Nonparametric State-Space Model for Multi-modal Dynamics Young-Jin Park Han-Lim Choi 9 0 0 19 Sep 2018
A Fourier View of REINFORCE Adeel Pervez 17 0 0 12 Aug 2018
A Review of Learning with Deep Generative Models from Perspective of Graphical Modeling Zhijian Ou 23 16 0 05 Aug 2018
ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks Mingzhang Yin Mingyuan Zhou MQ 26 11 0 30 Jul 2018
Latent Alignment and Variational Attention Yuntian Deng Yoon Kim Justin T. Chiu Demi Guo Alexander M. Rush BDL 18 110 0 10 Jul 2018
Adaptive Path-Integral Autoencoder: Representation Learning and Planning for Dynamical Systems Jung-Su Ha Young-Jin Park Hyeok-Joo Chae Soon-Seo Park Han-Lim Choi BDL 17 26 0 05 Jul 2018
Learning in Variational Autoencoders with Kullback-Leibler and Renyi Integral Bounds Septimia Sârbu Riccardo Volpi Alexandra Peste Luigi Malagò DRL 11 0 0 05 Jul 2018
Tensor Monte Carlo: particle methods for the GPU era Laurence Aitchison BDL DRL 11 13 0 22 Jun 2018
Accurate and Diverse Sampling of Sequences based on a "Best of Many" Sample Objective Apratim Bhattacharyya Bernt Schiele Mario Fritz 28 110 0 20 Jun 2018
Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects Adam R. Kosiorek Hyunjik Kim Ingmar Posner Yee Whye Teh BDL 23 256 0 05 Jun 2018
Reparameterization Gradient for Non-differentiable Models Wonyeol Lee Hangyeol Yu Hongseok Yang DRL 17 30 0 01 Jun 2018
Theory and Experiments on Vector Quantized Autoencoders Aurko Roy Ashish Vaswani Arvind Neelakantan Niki Parmar 11 85 0 28 May 2018
Flexible and accurate inference and learning for deep generative models Eszter Vértes M. Sahani SyDa BDL 11 44 0 28 May 2018
Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow T. Le Adam R. Kosiorek N. Siddharth Yee Whye Teh Frank D. Wood BDL 9 23 0 26 May 2018
DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors Arash Vahdat Evgeny Andriyash W. Macready 11 49 0 18 May 2018
GumBolt: Extending Gumbel trick to Boltzmann priors Amir Khoshaman Mohammad H. Amin 17 14 0 18 May 2018
Associative Compression Networks for Representation Learning Alex Graves Jacob Menick Aaron van den Oord CML 7 20 0 06 Apr 2018
Variational Rejection Sampling Aditya Grover Ramki Gummadi Miguel Lazaro-Gredilla Dale Schuurmans Stefano Ermon BDL 15 32 0 05 Apr 2018
Stochastic Variational Inference with Gradient Linearization Tobias Plötz Anne S. Wannenwetsch Stefan Roth 6 2 0 28 Mar 2018