Reweighted Wake-Sleep

11 June 2014

Papers citing "Reweighted Wake-Sleep"

50 / 51 papers shown

Title
Bridge the Inference Gaps of Neural Processes via Expectation Maximization Q. Wang Marco Federici H. V. Hoof UQCV BDL 51 13 0 08 Jan 2025
Improving Tree Probability Estimation with Stochastic Optimization and Variance Reduction Tianyu Xie Musu Yuan Minghua Deng Cheng Zhang 34 0 0 09 Sep 2024
Torchtree: flexible phylogenetic model development and inference using PyTorch Mathieu Fourment Matthew Macaulay Christiaan J. Swanepoel Xiang Ji M. Suchard Frederick A Matsen IV BDL 29 0 0 26 Jun 2024
Towards Model-Agnostic Posterior Approximation for Fast and Accurate Variational Autoencoders Yaniv Yacoby Weiwei Pan Finale Doshi-Velez DRL 29 0 0 13 Mar 2024
Improving Variational Autoencoder Estimation from Incomplete Data with Mixture Variational Families Vaidotas Šimkus Michael U. Gutmann 48 2 0 05 Mar 2024
Delta-AI: Local objectives for amortized inference in sparse graphical models Jean-Pierre Falet Hae Beom Lee Nikolay Malkin Chen Sun Dragos Secrieru Thomas Jiralerspong Dinghuai Zhang Guillaume Lajoie Yoshua Bengio 51 6 0 03 Oct 2023
Massively Parallel Reweighted Wake-Sleep Thomas Heap Gavin Leech Laurence Aitchison BDL 24 2 0 18 May 2023
U-Statistics for Importance-Weighted Variational Inference Javier Burroni Kenta Takatsu Justin Domke Daniel Sheldon 18 1 0 27 Feb 2023
Multi-level Data Representation For Training Deep Helmholtz Machines J. M. Ramos Luis Sa-Couto Andreas Wichert 18 0 0 26 Oct 2022
A Variational Perspective on Generative Flow Networks Heiko Zimmermann Fredrik Lindsten Jan-Willem van de Meent C. A. Naesseth 22 32 0 14 Oct 2022
GFlowNets and variational inference Nikolay Malkin Salem Lahlou T. Deleu Xu Ji J. E. Hu Katie Everett Dinghuai Zhang Yoshua Bengio BDL 136 78 0 02 Oct 2022
Tighter Variational Bounds are Not Necessarily Better. A Research Report on Implementation, Ablation Study, and Extensions Amine MĆharrak Vít Ruzicka Sangyun Shin M. Vankadari DRL 16 0 0 23 Sep 2022
Gradients should stay on Path: Better Estimators of the Reverse- and Forward KL Divergence for Normalizing Flows Lorenz Vaitl K. Nicoli Shinichi Nakajima Pan Kessel 61 24 0 17 Jul 2022
Path-Gradient Estimators for Continuous Normalizing Flows Lorenz Vaitl K. Nicoli Shinichi Nakajima Pan Kessel 27 13 0 17 Jun 2022
Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients Kyurae Kim Jisu Oh Jacob R. Gardner Adji Bousso Dieng Hongseok Kim BDL 37 8 0 13 Jun 2022
A Variational Approach to Bayesian Phylogenetic Inference Cheng Zhang IV FrederickA.Matsen BDL 24 17 0 16 Apr 2022
Transport Score Climbing: Variational Inference Using Forward KL and Adaptive Neural Transport Liyi Zhang David M. Blei C. A. Naesseth 30 6 0 03 Feb 2022
Learning cortical representations through perturbed and adversarial dreaming Nicolas Deperrois Mihai A. Petrovici Walter Senn Jakob Jordan GAN CLL 58 21 0 09 Sep 2021
Variational Refinement for Importance Sampling Using the Forward Kullback-Leibler Divergence Ghassen Jerfel S. Wang Clara Fannjiang Katherine A. Heller Yi Ma Michael I. Jordan BDL 30 40 0 30 Jun 2021
Nested Variational Inference Heiko Zimmermann Hao Wu Babak Esmaeili Jan-Willem van de Meent BDL 32 20 0 21 Jun 2021
Empirical Evaluation of Biased Methods for Alpha Divergence Minimization Tomas Geffner Justin Domke 30 9 0 13 May 2021
Planning from Pixels in Atari with Learned Symbolic Representations Andrea Dittadi Frederik K. Drachmann Thomas Bolander 26 11 0 16 Dec 2020
Joint Stochastic Approximation and Its Application to Learning Discrete Latent Variable Models Zhijian Ou Yunfu Song BDL 32 8 0 28 May 2020
Markovian Score Climbing: Variational Inference with KL(p\|\|q) C. A. Naesseth Fredrik Lindsten David M. Blei 123 54 0 23 Mar 2020
Amortised Learning by Wake-Sleep W. Li Theodore H. Moskovitz Heishiro Kanagawa M. Sahani OOD 23 7 0 22 Feb 2020
Composing Modeling and Inference Operations with Probabilistic Program Combinators Eli Sennesh Adam Scibior Hao Wu Jan-Willem van de Meent TPM 18 1 0 14 Nov 2018
A Review of Learning with Deep Generative Models from Perspective of Graphical Modeling Zhijian Ou 31 16 0 05 Aug 2018
Generative Modeling by Inclusive Neural Random Fields with Applications in Image Generation and Anomaly Detection Yunfu Song Zhijian Ou DiffM 14 30 0 01 Jun 2018
AMR Parsing as Graph Prediction with Latent Alignment Chunchuan Lyu Ivan Titov GNN BDL 19 127 0 14 May 2018
Regularizing Deep Neural Networks by Noise: Its Interpretation and Optimization Hyeonwoo Noh Tackgeun You Jonghwan Mun Bohyung Han NoLa 29 197 0 14 Oct 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
On Unifying Deep Generative Models Zhiting Hu Zichao Yang Ruslan Salakhutdinov Eric Xing DRL GAN 41 127 0 02 Jun 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
LogitBoost autoregressive networks M. Goessling TPM 18 5 0 22 Mar 2017
Boundary-Seeking Generative Adversarial Networks R. Devon Hjelm Athul Paul Jacob Tong Che Adam Trischler Kyunghyun Cho Yoshua Bengio GAN 23 170 0 27 Feb 2017
On the Origin of Deep Learning Haohan Wang Bhiksha Raj MedIm 3DV VLM 48 223 0 24 Feb 2017
Max-Margin Deep Generative Models for (Semi-)Supervised Learning Chongxuan Li Jun Zhu Bo Zhang AI4CE 32 42 0 22 Nov 2016
Unsupervised Learning with Truncated Gaussian Graphical Models Qinliang Su X. Liao Chunyuan Li Zhe Gan Lawrence Carin 18 8 0 15 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
Discrete Variational Autoencoders J. Rolfe BDL DRL 35 254 0 07 Sep 2016
Neural Autoregressive Distribution Estimation Benigno Uria Marc-Alexandre Côté Karol Gregor Iain Murray Hugo Larochelle 42 313 0 07 May 2016
Learning to Generate with Memory Chongxuan Li Jun Zhu Bo Zhang BDL 24 42 0 24 Feb 2016
Variational inference for Monte Carlo objectives A. Mnih Danilo Jimenez Rezende DRL BDL 52 288 0 22 Feb 2016
Online Semi-Supervised Learning with Deep Hybrid Boltzmann Machines and Denoising Autoencoders Alexander Ororbia C. Lee Giles David Reitter AI4CE 20 30 0 22 Nov 2015
Neural Variational Inference for Text Processing Yishu Miao Lei Yu Phil Blunsom VLM DRL 28 616 0 19 Nov 2015
MuProp: Unbiased Backpropagation for Stochastic Neural Networks S. Gu Sergey Levine Ilya Sutskever A. Mnih BDL 16 143 0 16 Nov 2015
Learning Wake-Sleep Recurrent Attention Models Jimmy Ba Roger C. Grosse Ruslan Salakhutdinov B. Frey BDL 32 65 0 22 Sep 2015
Importance Weighted Autoencoders Yuri Burda Roger C. Grosse Ruslan Salakhutdinov BDL 62 1,236 0 01 Sep 2015
Neural Adaptive Sequential Monte Carlo S. Gu Zoubin Ghahramani Richard Turner BDL 24 145 0 10 Jun 2015
Deep Unsupervised Learning using Nonequilibrium Thermodynamics Jascha Narain Sohl-Dickstein Eric A. Weiss Niru Maheswaranathan Surya Ganguli SyDa DiffM 103 6,635 0 12 Mar 2015