Importance Weighted Autoencoders

1 September 2015

Papers citing "Importance Weighted Autoencoders"

50 / 794 papers shown

Title
Bootstrapping Neural Processes Juho Lee Yoonho Lee Jungtaek Kim Eunho Yang Sung Ju Hwang Yee Whye Teh UQCV BDL 26 42 0 07 Aug 2020
Optimal Variance Control of the Score Function Gradient Estimator for Importance Weighted Bounds Valentin Liévin Andrea Dittadi Anders Christensen Ole Winther DRL 30 6 0 05 Aug 2020
SeismoFlow -- Data augmentation for the class imbalance problem R. Milidiú Luis Müller AI4TS 17 1 0 23 Jul 2020
Multi-Sample Online Learning for Probabilistic Spiking Neural Networks Hyeryung Jang Osvaldo Simeone 18 0 0 23 Jul 2020
Measurement error models: from nonparametric methods to deep neural networks Zhirui Hu Z. Ke Jun S. Liu 9 4 0 15 Jul 2020
Failure Modes of Variational Autoencoders and Their Effects on Downstream Tasks Yaniv Yacoby Weiwei Pan Finale Doshi-Velez CML DRL 32 25 0 14 Jul 2020
Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models K. Nicoli Christopher J. Anders L. Funcke T. Hartung K. Jansen Pan Kessel Shinichi Nakajima Paolo Stornati AI4CE 10 3 0 14 Jul 2020
Variational Inference with Continuously-Indexed Normalizing Flows Anthony L. Caterini R. Cornish Dino Sejdinovic Arnaud Doucet BDL 24 19 0 10 Jul 2020
Self-Reflective Variational Autoencoder Ifigeneia Apostolopoulou Elan Rosenfeld A. Dubrawski OOD BDL DRL 19 0 0 10 Jul 2020
NVAE: A Deep Hierarchical Variational Autoencoder Arash Vahdat Jan Kautz BDL 35 895 0 08 Jul 2020
Efficient Learning of Generative Models via Finite-Difference Score Matching Tianyu Pang Kun Xu Chongxuan Li Yang Song Stefano Ermon Jun Zhu DiffM 31 53 0 07 Jul 2020
Learning to learn generative programs with Memoised Wake-Sleep Luke B. Hewitt T. Le J. Tenenbaum CLL 22 26 0 06 Jul 2020
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows Didrik Nielsen P. Jaini Emiel Hoogeboom Ole Winther Max Welling TPM BDL DRL 23 88 0 06 Jul 2020
Efficient Marginalization of Discrete and Structured Latent Variables via Sparsity Gonçalo M. Correia Vlad Niculae Wilker Aziz André F. T. Martins BDL 30 22 0 03 Jul 2020
Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes Andrew Y. K. Foong W. Bruinsma Jonathan Gordon Yann Dubois James Requeima Richard Turner BDL 14 77 0 02 Jul 2020
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference Rob Brekelmans Vaden Masrani Frank Wood Greg Ver Steeg Aram Galstyan 22 16 0 01 Jul 2020
Semi-supervised Sequential Generative Models Michael Teng T. Le Adam Scibior Frank Wood BDL AI4TS 27 3 0 30 Jun 2020
Learning Sparse Prototypes for Text Generation Junxian He Taylor Berg-Kirkpatrick Graham Neubig 27 23 0 29 Jun 2020
Lattice Representation Learning Luis A. Lastras 22 1 0 24 Jun 2020
Learning Disentangled Representations of Video with Missing Data Armand Comas Massague Chi Zhang Z. Feric Mario Sznaier Rose Yu DRL 25 16 0 23 Jun 2020
not-MIWAE: Deep Generative Modelling with Missing not at Random Data Niels Bruun Ipsen Pierre-Alexandre Mattei J. Frellsen DRL 14 54 0 23 Jun 2020
Embodied Self-supervised Learning by Coordinated Sampling and Training Yifan Sun Xihong Wu SSL 14 7 0 20 Jun 2020
DisARM: An Antithetic Gradient Estimator for Binary Latent Variables Zhe Dong A. Mnih George Tucker DRL 16 32 0 18 Jun 2020
Variational Autoencoder with Learned Latent Structure Marissa Connor Gregory H. Canal Christopher Rozell CML DRL 34 42 0 18 Jun 2020
Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization Abhinav Agrawal Daniel Sheldon Justin Domke TPM BDL 19 38 0 18 Jun 2020
A Tutorial on VAEs: From Bayes' Rule to Lossless Compression Ronald Yu BDL 21 23 0 18 Jun 2020
Analytical Probability Distributions and EM-Learning for Deep Generative Networks Randall Balestriero Sébastien Paris Richard G. Baraniuk UQCV DRL 9 1 0 17 Jun 2020
Density Deconvolution with Normalizing Flows Tim Dockhorn James A. Ritchie Yaoliang Yu Iain Murray DRL 18 5 0 16 Jun 2020
Isometric Autoencoders Amos Gropp Matan Atzmon Y. Lipman DRL 21 18 0 16 Jun 2020
Density of States Estimation for Out-of-Distribution Detection Warren Morningstar Cusuh Ham Andrew Gallagher Balaji Lakshminarayanan Alexander A. Alemi Joshua V. Dillon OODD 24 84 0 16 Jun 2020
Multimodal Generative Learning Utilizing Jensen-Shannon-Divergence Thomas M. Sutter Imant Daunhawer Julia E. Vogt 39 67 0 15 Jun 2020
Hindsight Expectation Maximization for Goal-conditioned Reinforcement Learning Yunhao Tang A. Kucukelbir OffRL 27 16 0 13 Jun 2020
Manifold GPLVMs for discovering non-Euclidean latent structure in neural data Kristopher T. Jensen Ta-Chu Kao Marco Tripodi Guillaume Hennequin DRL 22 31 0 12 Jun 2020
Improving GAN Training with Probability Ratio Clipping and Sample Reweighting Yue Wu Pan Zhou A. Wilson Eric Xing Zhiting Hu GAN 31 33 0 12 Jun 2020
Cumulant GAN Yannis Pantazis D. Paul M. Fasoulakis Y. Stylianou Markos A. Katsoulakis GAN 16 18 0 11 Jun 2020
A Generalised Linear Model Framework for $β$ -Variational Autoencoders based on Exponential Dispersion Families Robert Sicks R. Korn Stefanie Schwaar 21 12 0 11 Jun 2020
Probabilistic Autoencoder Vanessa Böhm U. Seljak UQCV BDL DRL 24 32 0 09 Jun 2020
VAEs in the Presence of Missing Data Mark Collier A. Nazábal Christopher K. I. Williams DRL 20 29 0 09 Jun 2020
Super-resolution Variational Auto-Encoders Ioannis Gatopoulos M. Stol Jakub M. Tomczak SupR DiffM 25 15 0 09 Jun 2020
AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation Jae Hyun Lim Aaron Courville C. Pal Chin-Wei Huang DRL 8 23 0 09 Jun 2020
MHVAE: a Human-Inspired Deep Hierarchical Generative Model for Multimodal Representation Learning Miguel Vasco Francisco S. Melo Ana Paiva DRL 6 11 0 04 Jun 2020
Joint Stochastic Approximation and Its Application to Learning Discrete Latent Variable Models Zhijian Ou Yunfu Song BDL 34 8 0 28 May 2020
A Batch Normalized Inference Network Keeps the KL Vanishing Away Qile Zhu Jianlin Su Wei Bi Xiaojiang Liu Xiyao Ma Xiaolin Li D. Wu BDL DRL 42 61 0 27 Apr 2020
VOWEL: A Local Online Learning Rule for Recurrent Networks of Probabilistic Spiking Winner-Take-All Circuits Hyeryung Jang N. Skatchkovsky Osvaldo Simeone 32 11 0 20 Apr 2020
Do sequence-to-sequence VAEs learn global features of sentences? Tom Bosc Pascal Vincent SSL 23 9 0 16 Apr 2020
Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation Sajad Norouzi David J. Fleet Mohammad Norouzi VLM DRL 16 3 0 09 Apr 2020
Optimus: Organizing Sentences via Pre-trained Modeling of a Latent Space Chunyuan Li Xiang Gao Yuan Li Baolin Peng Xiujun Li Yizhe Zhang Jianfeng Gao SSL DRL 32 181 0 05 Apr 2020
Epitomic Variational Graph Autoencoder R. A. Khan Muhammad Umer Anwaar M. Kleinsteuber BDL 35 10 0 03 Apr 2020
SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models Yucen Luo Alex Beatson Mohammad Norouzi Jun Zhu David Duvenaud Ryan P. Adams Ricky T. Q. Chen 11 29 0 01 Apr 2020
MCFlow: Monte Carlo Flow Models for Data Imputation Trevor W. Richardson Wencheng Wu Lei Lin Beilei Xu Edgar A. Bernal OOD 14 45 0 27 Mar 2020