Variational Inference with Normalizing Flows

21 May 2015

Danilo Jimenez Rezende

Papers citing "Variational Inference with Normalizing Flows"

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Title
Structured Output Learning with Conditional Generative Flows You Lu Bert Huang BDL DRL 21 72 0 30 May 2019
Graph Normalizing Flows Jenny Liu Aviral Kumar Jimmy Ba J. Kiros Kevin Swersky BDL GNN AI4CE 27 154 0 30 May 2019
Walsh-Hadamard Variational Inference for Bayesian Deep Learning Simone Rossi Sébastien Marmin Maurizio Filippone BDL 32 14 0 27 May 2019
HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference Jakob Kruse Gianluca Detommaso Ullrich Kothe Robert Scheichl 13 45 0 25 May 2019
DIVA: Domain Invariant Variational Autoencoders Maximilian Ilse Jakub M. Tomczak Christos Louizos Max Welling DRL OOD 28 198 0 24 May 2019
Discrete Flows: Invertible Generative Models of Discrete Data Dustin Tran Keyon Vafa Kumar Krishna Agrawal Laurent Dinh Ben Poole DRL 24 114 0 24 May 2019
Non-Autoregressive Neural Text-to-Speech Kainan Peng Ming-Yu Liu Z. Song Kexin Zhao 29 39 0 21 May 2019
Minimal Achievable Sufficient Statistic Learning Milan Cvitkovic Günther Koliander 25 12 0 19 May 2019
Integer Discrete Flows and Lossless Compression Emiel Hoogeboom Jorn W. T. Peters Rianne van den Berg Max Welling 19 157 0 17 May 2019
Correlated Variational Auto-Encoders Da Tang Dawen Liang Tony Jebara Nicholas Ruozzi CML GNN 24 21 0 14 May 2019
Sum-of-Squares Polynomial Flow P. Jaini Kira A. Selby Yaoliang Yu TPM 22 141 0 07 May 2019
Neural source-filter waveform models for statistical parametric speech synthesis Xin Wang Shinji Takaki Junichi Yamagishi 31 117 0 27 Apr 2019
Effective Estimation of Deep Generative Language Models Tom Pelsmaeker Wilker Aziz BDL 24 27 0 17 Apr 2019
Learning Probabilistic Multi-Modal Actor Models for Vision-Based Robotic Grasping Mengyuan Yan A. Li Mrinal Kalakrishnan P. Pastor 15 18 0 15 Apr 2019
Exact Rate-Distortion in Autoencoders via Echo Noise Rob Brekelmans Daniel Moyer Aram Galstyan Greg Ver Steeg 24 17 0 15 Apr 2019
Nonparametric Density Estimation for High-Dimensional Data - Algorithms and Applications Zhipeng Wang D. W. Scott 22 69 0 30 Mar 2019
Wasserstein Dependency Measure for Representation Learning Sherjil Ozair Corey Lynch Yoshua Bengio Aaron van den Oord Sergey Levine P. Sermanet SSL DRL 30 116 0 28 Mar 2019
Topic-Guided Variational Autoencoders for Text Generation Wenlin Wang Zhe Gan Hongteng Xu Ruiyi Zhang Guoyin Wang Dinghan Shen Changyou Chen Lawrence Carin BDL 27 126 0 17 Mar 2019
Semantics Preserving Adversarial Learning Ousmane Amadou Dia Elnaz Barshan Reza Babanezhad AAML GAN 29 2 0 10 Mar 2019
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport Matthew Hoffman Pavel Sountsov Joshua V. Dillon I. Langmore Dustin Tran Srinivas Vasudevan BDL 27 103 0 09 Mar 2019
VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation Manoj Kumar Mohammad Babaeizadeh D. Erhan Chelsea Finn Sergey Levine Laurent Dinh Durk Kingma VGen 25 131 0 04 Mar 2019
Conditional Density Estimation with Neural Networks: Best Practices and Benchmarks Jonas Rothfuss Fabio Ferreira Simon Walther Maxim Ulrich TPM 24 73 0 03 Mar 2019
Emerging Convolutions for Generative Normalizing Flows Emiel Hoogeboom Rianne van den Berg Max Welling DRL 13 98 0 30 Jan 2019
Discretizing Continuous Action Space for On-Policy Optimization Yunhao Tang Shipra Agrawal OffRL 26 118 0 29 Jan 2019
Deep Generative Learning via Variational Gradient Flow Yuan Gao Yuling Jiao Yang Wang Yao Wang Can Yang Shunkang Zhang 27 36 0 24 Jan 2019
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data Yinhao Zhu N. Zabaras P. Koutsourelakis P. Perdikaris PINN AI4CE 46 854 0 18 Jan 2019
Conditional deep surrogate models for stochastic, high-dimensional, and multi-fidelity systems Yibo Yang P. Perdikaris SyDa BDL AI4CE 29 55 0 15 Jan 2019
Dirichlet Variational Autoencoder Weonyoung Joo Wonsung Lee Sungrae Park Il-Chul Moon BDL DRL 19 101 0 09 Jan 2019
MAE: Mutual Posterior-Divergence Regularization for Variational AutoEncoders Xuezhe Ma Chunting Zhou Eduard H. Hovy DRL 20 39 0 06 Jan 2019
AdaFlow: Domain-Adaptive Density Estimator with Application to Anomaly Detection and Unpaired Cross-Domain Translation Masataka Yamaguchi Yuma Koizumi N. Harada 19 37 0 14 Dec 2018
Encoding prior knowledge in the structure of the likelihood Jakob Knollmüller T. Ensslin 36 11 0 11 Dec 2018
Partitioned Variational Inference: A unified framework encompassing federated and continual learning T. Bui Cuong V Nguyen S. Swaroop Richard Turner FedML 24 55 0 27 Nov 2018
Learning Attractor Dynamics for Generative Memory Yan Wu Greg Wayne Karol Gregor Timothy Lillicrap BDL 19 18 0 23 Nov 2018
Spread Divergence Mingtian Zhang Peter Hayes Thomas Bird Raza Habib David Barber MedIm UD 30 20 0 21 Nov 2018
Invertible Residual Networks Jens Behrmann Will Grathwohl Ricky T. Q. Chen David Duvenaud J. Jacobsen UQCV TPM 25 618 0 02 Nov 2018
Hybrid Generative-Discriminative Models for Inverse Materials Design Phuoc Nguyen T. Tran Sunil R. Gupta Santu Rana Svetha Venkatesh AI4CE PINN 13 6 0 31 Oct 2018
Resampled Priors for Variational Autoencoders Matthias Bauer A. Mnih BDL DRL 16 110 0 26 Oct 2018
Good Initializations of Variational Bayes for Deep Models Simone Rossi Pietro Michiardi Maurizio Filippone BDL 17 21 0 18 Oct 2018
Metropolis-Hastings view on variational inference and adversarial training Kirill Neklyudov Evgenii Egorov Pavel Shvechikov Dmitry Vetrov GAN 29 13 0 16 Oct 2018
Deep Generative Video Compression Jun Han Salvator Lombardo Christopher Schroers Stephan Mandt VGen 32 58 0 05 Oct 2018
WAIC, but Why? Generative Ensembles for Robust Anomaly Detection Hyun-Jae Choi Eric Jang Alexander A. Alemi OODD 20 82 0 02 Oct 2018
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models Will Grathwohl Ricky T. Q. Chen J. Bettencourt Ilya Sutskever David Duvenaud DRL 17 849 0 02 Oct 2018
Probabilistic Meta-Representations Of Neural Networks Theofanis Karaletsos Peter Dayan Zoubin Ghahramani BDL 12 27 0 01 Oct 2018
Variational Autoencoder with Implicit Optimal Priors Hiroshi Takahashi Tomoharu Iwata Yuki Yamanaka Masanori Yamada Satoshi Yagi DRL 34 61 0 14 Sep 2018
Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning Ilya Kostrikov Kumar Krishna Agrawal Debidatta Dwibedi Sergey Levine Jonathan Tompson 35 256 0 09 Sep 2018
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory Jianyi Zhang Ruiyi Zhang Lawrence Carin Changyou Chen 12 46 0 05 Sep 2018
Analyzing Inverse Problems with Invertible Neural Networks Lynton Ardizzone Jakob Kruse Sebastian J. Wirkert D. Rahner E. Pellegrini R. Klessen Lena Maier-Hein Carsten Rother Ullrich Kothe 21 483 0 14 Aug 2018
A Review of Learning with Deep Generative Models from Perspective of Graphical Modeling Zhijian Ou 31 16 0 05 Aug 2018
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model A. G. Baydin Lukas Heinrich W. Bhimji Lei Shao Saeid Naderiparizi ... Philip Torr Victor W. Lee P. Prabhat Kyle Cranmer Frank Wood 26 31 0 20 Jul 2018
Explorations in Homeomorphic Variational Auto-Encoding Luca Falorsi P. D. Haan Tim R. Davidson Nicola De Cao Maurice Weiler Patrick Forré Taco S. Cohen BDL DRL 30 116 0 12 Jul 2018