Importance Weighted Autoencoders

1 September 2015

Papers citing "Importance Weighted Autoencoders"

50 / 794 papers shown

Title
Linear Classifiers in Product Space Forms Puoya Tabaghi Chao Pan Eli Chien Jianhao Peng Olgica Milenković 32 9 0 19 Feb 2021
VAE Approximation Error: ELBO and Exponential Families Alexander Shekhovtsov D. Schlesinger B. Flach DRL 40 15 0 18 Feb 2021
Preventing Oversmoothing in VAE via Generalized Variance Parameterization Yuhta Takida Wei-Hsiang Liao Chieh-Hsin Lai Toshimitsu Uesaka Shusuke Takahashi Yuki Mitsufuji DRL 49 13 0 17 Feb 2021
Hierarchical VAEs Know What They Don't Know Jakob Drachmann Havtorn J. Frellsen Søren Hauberg Lars Maaløe DRL 37 72 0 16 Feb 2021
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport Adrien Corenflos James Thornton George Deligiannidis Arnaud Doucet OT 48 66 0 15 Feb 2021
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions Emiel Hoogeboom Didrik Nielsen P. Jaini Patrick Forré Max Welling DiffM 222 402 0 10 Feb 2021
Reducing the Amortization Gap in Variational Autoencoders: A Bayesian Random Function Approach Minyoung Kim Vladimir Pavlovic BDL 36 6 0 05 Feb 2021
Neural representation and generation for RNA secondary structures Zichao Yan William L. Hamilton Mathieu Blanchette 40 2 0 01 Feb 2021
Learning Interpretable Deep State Space Model for Probabilistic Time Series Forecasting Longyuan Li Junchi Yan Xiaokang Yang Yaohui Jin OOD BDL AI4TS 47 60 0 31 Jan 2021
Estimating the Unique Information of Continuous Variables Ari Pakman Amin Nejatbakhsh D. Gilboa Abdullah Makkeh Luca Mazzucato Michael Wibral E. Schneidman 45 24 0 30 Jan 2021
Generalized Doubly Reparameterized Gradient Estimators Matthias Bauer A. Mnih BDL 13 14 0 26 Jan 2021
Unsupervised Imputation of Non-ignorably Missing Data Using Importance-Weighted Autoencoders David K. Lim N. Rashid Junier B. Oliva J. Ibrahim 31 3 0 18 Jan 2021
Multimodal Variational Autoencoders for Semi-Supervised Learning: In Defense of Product-of-Experts S. Kutuzova Oswin Krause D. McCloskey Mads Nielsen Christian Igel 13 17 0 18 Jan 2021
Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models Justin Bayer Maximilian Soelch Atanas Mirchev Baris Kayalibay Patrick van der Smagt 29 15 0 18 Jan 2021
Cauchy-Schwarz Regularized Autoencoder Linh-Tam Tran Maja Pantic M. Deisenroth DRL BDL 24 17 0 06 Jan 2021
A Tutorial on Sparse Gaussian Processes and Variational Inference Felix Leibfried Vincent Dutordoir S. T. John N. Durrande GP 42 49 0 27 Dec 2020
Variational Determinant Estimation with Spherical Normalizing Flows Simon Passenheim Emiel Hoogeboom BDL 31 1 0 24 Dec 2020
Unsupervised Learning of Global Factors in Deep Generative Models I. Peis Pablo Martínez Olmos Antonio Artés-Rodríguez BDL DRL 34 8 0 15 Dec 2020
Recursive Tree Grammar Autoencoders Benjamin Paassen I. Koprinska K. Yacef 22 8 0 03 Dec 2020
Mutual Information Constraints for Monte-Carlo Objectives Gábor Melis András Gyorgy Phil Blunsom 21 1 0 01 Dec 2020
Improved Variational Bayesian Phylogenetic Inference with Normalizing Flows Cheng Zhang BDL 37 27 0 01 Dec 2020
Recursive Inference for Variational Autoencoders Minyoung Kim Vladimir Pavlovic DRL 8 13 0 17 Nov 2020
Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference M. Vandegar Michael Kagan Antoine Wehenkel Gilles Louppe 34 27 0 11 Nov 2020
On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes Tim G. J. Rudner Oscar Key Y. Gal Tom Rainforth 10 3 0 01 Nov 2020
Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective Vu-Linh Nguyen Vaden Masrani Rob Brekelmans Michael A. Osborne Frank Wood 24 5 0 29 Oct 2020
Generative Neurosymbolic Machines Jindong Jiang Sungjin Ahn BDL OCL 225 68 0 23 Oct 2020
Geometry-Aware Hamiltonian Variational Auto-Encoder Clément Chadebec Clément Mantoux S. Allassonnière DRL 24 15 0 22 Oct 2020
PAC $^m$ -Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime Warren Morningstar Alexander A. Alemi Joshua V. Dillon 87 16 0 19 Oct 2020
On the Difficulty of Unbiased Alpha Divergence Minimization Tomas Geffner Justin Domke 65 18 0 19 Oct 2020
Ensemble Kalman Variational Objectives: Nonlinear Latent Trajectory Inference with A Hybrid of Variational Inference and Ensemble Kalman Filter Tsuyoshi Ishizone T. Higuchi Kazuyuki Nakamura BDL 16 1 0 17 Oct 2020
Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models Fan Bao Kun Xu Chongxuan Li Lanqing Hong Jun Zhu Bo Zhang DiffM 22 8 0 16 Oct 2020
Controlling the Interaction Between Generation and Inference in Semi-Supervised Variational Autoencoders Using Importance Weighting G. Felhi Joseph Leroux Djamé Seddah BDL 28 1 0 13 Oct 2020
Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator Max B. Paulus Chris J. Maddison Andreas Krause BDL 44 38 0 09 Oct 2020
Uncertainty in Neural Processes Saeid Naderiparizi Ke-Li Chiu Benjamin Bloem-Reddy Frank Wood UQCV BDL AI4CE 11 4 0 08 Oct 2020
Learning Deep-Latent Hierarchies by Stacking Wasserstein Autoencoders Benoit Gaujac Ilya Feige David Barber DiffM BDL 28 0 0 07 Oct 2020
Narrative Text Generation with a Latent Discrete Plan Harsh Jhamtani Taylor Berg-Kirkpatrick 16 17 0 07 Oct 2020
Scalable Normalizing Flows for Permutation Invariant Densities Marin Bilos Stephan Günnemann TPM 19 23 0 07 Oct 2020
Self-Supervised Variational Auto-Encoders Ioannis Gatopoulos Jakub M. Tomczak 37 13 0 05 Oct 2020
Unbiased Gradient Estimation for Variational Auto-Encoders using Coupled Markov Chains Francisco J. R. Ruiz Michalis K. Titsias taylan. cemgil Arnaud Doucet BDL DRL 12 14 0 05 Oct 2020
MCMC-Interactive Variational Inference Quan Zhang Huangjie Zheng Mingyuan Zhou 22 1 0 02 Oct 2020
Encoded Prior Sliced Wasserstein AutoEncoder for learning latent manifold representations Sanjukta Krishnagopal J. Bedrossian DRL 23 0 0 02 Oct 2020
VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models Zhisheng Xiao Karsten Kreis Jan Kautz Arash Vahdat 16 123 0 01 Oct 2020
f-Divergence Variational Inference Neng Wan Dapeng Li N. Hovakimyan 10 32 0 28 Sep 2020
Independent finite approximations for Bayesian nonparametric inference Tin D. Nguyen Jonathan H. Huggins L. Masoero Lester W. Mackey Tamara Broderick TPM 23 4 0 22 Sep 2020
Discond-VAE: Disentangling Continuous Factors from the Discrete Jaewoong Choi Geonho Hwang Myung-joo Kang CoGe CML 12 4 0 17 Sep 2020
Variational Deep Learning for the Identification and Reconstruction of Chaotic and Stochastic Dynamical Systems from Noisy and Partial Observations Duong Nguyen Said Ouala Lucas Drumetz Ronan Fablet 15 13 0 04 Sep 2020
LaDDer: Latent Data Distribution Modelling with a Generative Prior Shuyu Lin R. Clark DRL 21 4 0 31 Aug 2020
Modulating Scalable Gaussian Processes for Expressive Statistical Learning Haitao Liu Yew-Soon Ong Xiaomo Jiang Xiaofang Wang 23 4 0 29 Aug 2020
Decoupled Variational Embedding for Signed Directed Networks Xu Chen Jiangchao Yao Maosen Li Ya Zhang Yanfeng Wang 22 4 0 28 Aug 2020
Learning from Irregularly-Sampled Time Series: A Missing Data Perspective Steven Cheng-Xian Li Benjamin M. Marlin AI4TS 25 56 0 17 Aug 2020