Variational Inference with Normalizing Flows

21 May 2015

Danilo Jimenez Rezende

Papers citing "Variational Inference with Normalizing Flows"

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Title
Greedy inference with structure-exploiting lazy maps Michael C. Brennan Daniele Bigoni O. Zahm Alessio Spantini Youssef Marzouk 22 13 0 31 May 2019
On the Necessity and Effectiveness of Learning the Prior of Variational Auto-Encoder Haowen Xu Wenxiao Chen Jinlin Lai Zhihan Li Youjian Zhao Dan Pei DRL BDL 32 14 0 31 May 2019
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 27 155 0 30 May 2019
Replica-exchange Nosé-Hoover dynamics for Bayesian learning on large datasets Rui Luo Qiang Zhang Yaodong Yang Jun Wang BDL 30 3 0 29 May 2019
Generative Parameter Sampler For Scalable Uncertainty Quantification Minsuk Shin Young Lee Jun S. Liu 9 0 0 28 May 2019
Walsh-Hadamard Variational Inference for Bayesian Deep Learning Simone Rossi Sébastien Marmin Maurizio Filippone BDL 32 14 0 27 May 2019
ODE $^2$ VAE: Deep generative second order ODEs with Bayesian neural networks Çağatay Yıldız Markus Heinonen Harri Lähdesmäki BDL DRL 27 88 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
The Variational InfoMax AutoEncoder Vincenzo Crescimanna Bruce P. Graham DRL 14 3 0 25 May 2019
DIVA: Domain Invariant Variational Autoencoders Maximilian Ilse Jakub M. Tomczak Christos Louizos Max Welling DRL OOD 33 198 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 27 158 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 22 142 0 07 May 2019
Neural source-filter waveform models for statistical parametric speech synthesis Xin Wang Shinji Takaki Junichi Yamagishi 40 117 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 24 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 30 126 0 17 Mar 2019
MSG-GAN: Multi-Scale Gradients for Generative Adversarial Networks Animesh Karnewar Oliver Wang GAN 16 50 0 14 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 29 73 0 03 Mar 2019
Emerging Convolutions for Generative Normalizing Flows Emiel Hoogeboom Rianne van den Berg Max Welling DRL 24 98 0 30 Jan 2019
Latent Normalizing Flows for Discrete Sequences Zachary M. Ziegler Alexander M. Rush BDL DRL 27 122 0 29 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 27 101 0 09 Jan 2019
MAE: Mutual Posterior-Divergence Regularization for Variational AutoEncoders Xuezhe Ma Chunting Zhou Eduard H. Hovy DRL 28 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 22 37 0 14 Dec 2018
Encoding prior knowledge in the structure of the likelihood Jakob Knollmüller T. Ensslin 38 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 27 55 0 27 Nov 2018
Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples with Applications to Neuroimaging Seong Jae Hwang Zirui Tao Won Hwa Kim Vikas Singh MedIm 17 12 0 24 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
Adversarial Uncertainty Quantification in Physics-Informed Neural Networks Yibo Yang P. Perdikaris AI4CE PINN 20 355 0 09 Nov 2018
Invertible Residual Networks Jens Behrmann Will Grathwohl Ricky T. Q. Chen David Duvenaud J. Jacobsen UQCV TPM 34 618 0 02 Nov 2018
WaveGlow: A Flow-based Generative Network for Speech Synthesis R. Prenger Rafael Valle Bryan Catanzaro 49 1,023 0 31 Oct 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 22 110 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