Importance Weighted Autoencoders

1 September 2015

Papers citing "Importance Weighted Autoencoders"

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Title
Unpacking Information Bottlenecks: Unifying Information-Theoretic Objectives in Deep Learning Andreas Kirsch Clare Lyle Y. Gal 27 16 0 27 Mar 2020
Markovian Score Climbing: Variational Inference with KL(p\|\|q) C. A. Naesseth Fredrik Lindsten David M. Blei 123 54 0 23 Mar 2020
Social Navigation with Human Empowerment driven Deep Reinforcement Learning T. V. D. Heiden Christian Weiss H. V. Hoof 19 13 0 18 Mar 2020
Autoencoders Dor Bank Noam Koenigstein Raja Giryes HAI 13 0 0 12 Mar 2020
VMLoc: Variational Fusion For Learning-Based Multimodal Camera Localization Kaichen Zhou Changhao Chen Bing Wang Muhamad Risqi U. Saputra Niki Trigoni Andrew Markham 13 20 0 12 Mar 2020
Variational Learning of Individual Survival Distributions Zidi Xiu Chenyang Tao Benjamin A. Goldstein Ricardo Henao OOD 8 15 0 09 Mar 2020
Scalable Approximate Inference and Some Applications Jun Han BDL 27 1 0 07 Mar 2020
Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder Zhisheng Xiao Qing Yan Y. Amit OODD 20 189 0 06 Mar 2020
Automatic Differentiation Variational Inference with Mixtures Warren Morningstar Sharad M. Vikram Cusuh Ham Andrew Gallagher Joshua V. Dillon DRL BDL 20 20 0 03 Mar 2020
Curriculum By Smoothing Samarth Sinha Animesh Garg Hugo Larochelle 11 7 0 03 Mar 2020
Predictive Coding for Locally-Linear Control Rui Shu Tung D. Nguyen Yinlam Chow Tu Pham Khoat Than Mohammad Ghavamzadeh Stefano Ermon Hung Bui OffRL BDL 44 24 0 02 Mar 2020
Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows Ruizhi Deng B. Chang Marcus A. Brubaker Greg Mori Andreas M. Lehrmann 25 50 0 24 Feb 2020
Variational Hyper RNN for Sequence Modeling Ruizhi Deng Yanshuai Cao B. Chang Leonid Sigal Greg Mori Marcus A. Brubaker BDL DRL 20 2 0 24 Feb 2020
Variance Loss in Variational Autoencoders Andrea Asperti DRL 27 14 0 23 Feb 2020
Amortised Learning by Wake-Sleep W. Li Theodore H. Moskovitz Heishiro Kanagawa M. Sahani OOD 23 7 0 22 Feb 2020
Balancing reconstruction error and Kullback-Leibler divergence in Variational Autoencoders Andrea Asperti Matteo Trentin DRL 27 96 0 18 Feb 2020
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 42 10,591 0 17 Feb 2020
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models Chin-Wei Huang Laurent Dinh Aaron Courville DRL 31 87 0 17 Feb 2020
Latent Variable Modelling with Hyperbolic Normalizing Flows A. Bose Ariella Smofsky Renjie Liao Prakash Panangaden William L. Hamilton DRL 19 67 0 15 Feb 2020
Stochastic Approximate Gradient Descent via the Langevin Algorithm Yixuan Qiu Tianlin Li 22 4 0 13 Feb 2020
Deep Learning for Source Code Modeling and Generation: Models, Applications and Challenges T. H. Le Hao Chen Muhammad Ali Babar VLM 64 152 0 13 Feb 2020
Learning Flat Latent Manifolds with VAEs Nutan Chen Alexej Klushyn Francesco Ferroni Justin Bayer Patrick van der Smagt DRL 37 39 0 12 Feb 2020
Missing Data Imputation using Optimal Transport Boris Muzellec Julie Josse Claire Boyer Marco Cuturi OT 28 116 0 10 Feb 2020
Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow Didrik Nielsen Ole Winther MQ 201 13 0 06 Feb 2020
Learning Discrete Distributions by Dequantization Emiel Hoogeboom Taco S. Cohen Jakub M. Tomczak DRL 34 31 0 30 Jan 2020
A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor Analysis Christopher J. Urban Daniel J. Bauer BDL 12 33 0 22 Jan 2020
Joint Distributions for TensorFlow Probability Dan Piponi Dave Moore Joshua V. Dillon GP 27 16 0 22 Jan 2020
Approximating Activation Functions Nicholas Gerard Timmons Andrew Rice 25 14 0 17 Jan 2020
Invertible Generative Modeling using Linear Rational Splines H. M. Dolatabadi S. Erfani C. Leckie 40 65 0 15 Jan 2020
Efficient Debiased Evidence Estimation by Multilevel Monte Carlo Sampling Kei Ishikawa T. Goda 8 2 0 14 Jan 2020
AE-OT-GAN: Training GANs from data specific latent distribution Dongsheng An Yang Guo Min Zhang Xin Qi Na Lei S. Yau X. Gu DRL GAN 32 24 0 11 Jan 2020
A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning Soochan Lee Junsoo Ha Dongsu Zhang Gunhee Kim BDL CLL 25 210 0 03 Jan 2020
Hierarchical Variational Imitation Learning of Control Programs Roy Fox Richard Shin William Paul Yitian Zou D. Song Ken Goldberg Pieter Abbeel Ion Stoica BDL 22 4 0 29 Dec 2019
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse Bin Dai Ziyu Wang David Wipf DRL 26 75 0 23 Dec 2019
Multilevel Monte Carlo estimation of log marginal likelihood T. Goda Kei Ishikawa 20 3 0 23 Dec 2019
Learning Representations by Maximizing Mutual Information in Variational Autoencoders Ali Lotfi-Rezaabad S. Vishwanath DRL SSL 22 39 0 21 Dec 2019
Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax Andres Potapczynski Gabriel Loaiza-Ganem John P. Cunningham 32 29 0 19 Dec 2019
Bayesian Variational Autoencoders for Unsupervised Out-of-Distribution Detection Erik A. Daxberger José Miguel Hernández-Lobato UQCV 18 63 0 11 Dec 2019
Neural Networks with Cheap Differential Operators Ricky T. Q. Chen David Duvenaud 20 34 0 08 Dec 2019
Stochastic Variational Inference via Upper Bound Chunlin Ji Haige Shen UQCV BDL 26 11 0 02 Dec 2019
Improving VAE generations of multimodal data through data-dependent conditional priors Frantzeska Lavda Magda Gregorova Alexandros Kalousis 8 4 0 25 Nov 2019
Mixed-curvature Variational Autoencoders Ondrej Skopek O. Ganea Gary Bécigneul CML DRL BDL 30 101 0 19 Nov 2019
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models Tong Che Xiaofeng Liu Site Li Yubin Ge Ruixiang Zhang Caiming Xiong Yoshua Bengio 38 52 0 18 Nov 2019
Rate-Regularization and Generalization in VAEs Alican Bozkurt Babak Esmaeili Jean-Baptiste Tristan Dana H. Brooks Jennifer G. Dy Jan-Willem van de Meent DRL 38 7 0 11 Nov 2019
On Posterior Collapse and Encoder Feature Dispersion in Sequence VAEs Teng Long Yanshuai Cao Jackie C.K. Cheung 22 6 0 10 Nov 2019
Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models Yuge Shi Siddharth Narayanaswamy Brooks Paige Philip Torr DRL 32 266 0 08 Nov 2019
Amortized Population Gibbs Samplers with Neural Sufficient Statistics Hao Wu Heiko Zimmermann Eli Sennesh T. Le Jan-Willem van de Meent 25 7 0 04 Nov 2019
Multiple Futures Prediction Yichuan Tang Ruslan Salakhutdinov 39 348 0 04 Nov 2019
A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal Experiments Adam Foster M. Jankowiak M. O'Meara Yee Whye Teh Tom Rainforth BDL 24 59 0 01 Nov 2019
Continual Unsupervised Representation Learning Dushyant Rao Francesco Visin Andrei A. Rusu Yee Whye Teh Razvan Pascanu R. Hadsell BDL CLL SSL DRL 6 256 0 31 Oct 2019