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Variational Inference with Normalizing Flows

21 May 2015

Danilo Jimenez Rezende

Papers citing "Variational Inference with Normalizing Flows"

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Title
Weight of Evidence as a Basis for Human-Oriented Explanations David Alvarez-Melis Hal Daumé Jennifer Wortman Vaughan Hanna M. Wallach XAI FAtt 91 20 0 29 Oct 2019
Neural Density Estimation and Likelihood-free Inference George Papamakarios BDL DRL 100 47 0 29 Oct 2019
Reversible designs for extreme memory cost reduction of CNN training T. Hascoet Q. Febvre Y. Ariki T. Takiguchi 3DV 15 2 0 24 Oct 2019
Point Process Flows Nazanin Mehrasa Ruizhi Deng Mohamed Osama Ahmed B. Chang Jiawei He Thibaut Durand Marcus A. Brubaker Greg Mori AI4TS 66 9 0 18 Oct 2019
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction Ajay Jain Sergio Casas Renjie Liao Yuwen Xiong Song Feng Sean Segal R. Urtasun 226 73 0 17 Oct 2019
MAVEN: Multi-Agent Variational Exploration Anuj Mahajan Tabish Rashid Mikayel Samvelyan Shimon Whiteson DRL 216 366 0 16 Oct 2019
The Renyi Gaussian Process: Towards Improved Generalization Xubo Yue Raed Al Kontar 140 3 0 15 Oct 2019
MIM: Mutual Information Machine M. Livne Kevin Swersky David J. Fleet DRL 47 6 0 08 Oct 2019
Quantum Hamiltonian-Based Models and the Variational Quantum Thermalizer Algorithm Guillaume Verdon Jacob A. Marks Sasha Nanda Stefan Leichenauer Jack Hidary DRL 80 99 0 04 Oct 2019
The Neural Moving Average Model for Scalable Variational Inference of State Space Models Tom Ryder D. Prangle Andrew Golightly Isaac Matthews BDL AI4TS 92 6 0 02 Oct 2019
Equivariant Flows: sampling configurations for multi-body systems with symmetric energies Jonas Köhler Leon Klein Frank Noé 91 91 0 02 Oct 2019
Tightening Bounds for Variational Inference by Revisiting Perturbation Theory Robert Bamler Cheng Zhang Manfred Opper Stephan Mandt 48 3 0 30 Sep 2019
Neural Canonical Transformation with Symplectic Flows Shuo-Hui Li Chen Dong Linfeng Zhang Lei Wang DRL 119 28 0 30 Sep 2019
Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows R. Cornish Anthony L. Caterini George Deligiannidis Arnaud Doucet 50 3 0 30 Sep 2019
Hamiltonian Generative Networks Peter Toth Danilo Jimenez Rezende Andrew Jaegle S. Racanière Aleksandar Botev I. Higgins BDL DRL AI4CE GAN 79 218 0 30 Sep 2019
Equivariant Hamiltonian Flows Danilo Jimenez Rezende S. Racanière I. Higgins Peter Toth 91 64 0 30 Sep 2019
Wasserstein-2 Generative Networks Alexander Korotin Vage Egiazarian Arip Asadulaev Alexander Safin Evgeny Burnaev GAN 255 109 0 28 Sep 2019
Identifying through Flows for Recovering Latent Representations Shen Li Bryan Hooi Gim Hee Lee DRL OOD 106 14 0 27 Sep 2019
Intensity-Free Learning of Temporal Point Processes Oleksandr Shchur Marin Bilos Stephan Günnemann AI4TS 95 172 0 26 Sep 2019
Prediction of rare feature combinations in population synthesis: Application of deep generative modelling Sergio Garrido S. Borysov Francisco Câmara Pereira Jeppe Rich 50 42 0 17 Sep 2019
A Characteristic Function Approach to Deep Implicit Generative Modeling Abdul Fatir Ansari Jonathan Scarlett Harold Soh VLM GAN 53 40 0 16 Sep 2019
$ρ$ -VAE: Autoregressive parametrization of the VAE encoder Sohrab Ferdowsi M. Diephuis Shideh Rezaeifar Svyatoslav Voloshynovskiy 29 3 0 13 Sep 2019
Balancing Reconstruction Quality and Regularisation in ELBO for VAEs Shuyu Lin Stephen J. Roberts Niki Trigoni R. Clark DRL 43 16 0 09 Sep 2019
Neural Gaussian Copula for Variational Autoencoder P. Wang William Yang Wang BDL DRL 53 13 0 09 Sep 2019
Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation Konstantinos Pitas 75 8 0 06 Sep 2019
FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow Xuezhe Ma Chunting Zhou Xian Li Graham Neubig Eduard H. Hovy AI4TS BDL 90 192 0 05 Sep 2019
Accelerated Information Gradient flow Yifei Wang Wuchen Li 86 57 0 04 Sep 2019
Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning Johann Brehmer S. Mishra-Sharma Joeri Hermans Gilles Louppe Kyle Cranmer 114 74 0 04 Sep 2019
Towards Interpretable Polyphonic Transcription with Invertible Neural Networks Rainer Kelz Gerhard Widmer 44 15 0 04 Sep 2019
A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text Bohan Li Junxian He Graham Neubig Taylor Berg-Kirkpatrick Yiming Yang DRL 59 71 0 02 Sep 2019
Potential Flow Generator with $L_2$ Optimal Transport Regularity for Generative Models Liu Yang George Karniadakis OT 67 43 0 29 Aug 2019
Flexible Conditional Image Generation of Missing Data with Learned Mental Maps Benjamin Hou Athanasios Vlontzos A. Alansary Daniel Rueckert Bernhard Kainz MedIm 26 1 0 29 Aug 2019
PixelVAE++: Improved PixelVAE with Discrete Prior Hossein Sadeghi Evgeny Andriyash W. Vinci L. Buffoni Mohammad H. Amin BDL DRL 53 33 0 26 Aug 2019
Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Víctor Gallego D. Insua BDL 55 1 0 26 Aug 2019
Normalizing Flows: An Introduction and Review of Current Methods I. Kobyzev S. Prince Marcus A. Brubaker TPM MedIm 100 58 0 25 Aug 2019
Conditional Flow Variational Autoencoders for Structured Sequence Prediction Apratim Bhattacharyya M. Hanselmann Mario Fritz Bernt Schiele C. Straehle BDL DRL AI4TS 110 86 0 24 Aug 2019
Calibration of Deep Probabilistic Models with Decoupled Bayesian Neural Networks Juan Maroñas Roberto Paredes Palacios D. Ramos-Castro UQCV BDL 102 24 0 23 Aug 2019
Noise Flow: Noise Modeling with Conditional Normalizing Flows A. Abdelhamed Marcus A. Brubaker M. S. Brown 75 174 0 22 Aug 2019
DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer Haoliang Sun Ronak R. Mehta H. Zhou Z. Huang Sterling C. Johnson V. Prabhakaran Vikas Singh MedIm 106 46 0 21 Aug 2019
Semi-Implicit Graph Variational Auto-Encoders Arman Hasanzadeh Ehsan Hajiramezanali N. Duffield Krishna R. Narayanan Mingyuan Zhou Xiaoning Qian BDL GNN 88 132 0 19 Aug 2019
Unconstrained Monotonic Neural Networks Antoine Wehenkel Gilles Louppe TPM 269 150 0 14 Aug 2019
Variational Bayes on Manifolds Minh-Ngoc Tran D. Nguyen Duy Nguyen 118 23 0 08 Aug 2019
Likelihood Contribution based Multi-scale Architecture for Generative Flows Hari Prasanna Das Pieter Abbeel C. Spanos DRL AI4CE 59 5 0 05 Aug 2019
Probabilistic Residual Learning for Aleatoric Uncertainty in Image Restoration Chen Zhang Bangti Jin UQCV 92 12 0 01 Aug 2019
Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement Ryutaro Tanno Daniel E. Worrall Enrico Kaden Aurobrata Ghosh Francesco Grussu A. Bizzi S. Sotiropoulos A. Criminisi Daniel C. Alexander MedIm DiffM 104 33 0 31 Jul 2019
Approximation Capabilities of Neural ODEs and Invertible Residual Networks Han Zhang Xi Gao Jacob Unterman Tom Arodz 90 100 0 30 Jul 2019
MadMiner: Machine learning-based inference for particle physics Johann Brehmer F. Kling Irina Espejo Kyle Cranmer 81 115 0 24 Jul 2019
Transport Monte Carlo: High-Accuracy Posterior Approximation via Random Transport L. Duan OT 61 11 0 24 Jul 2019
Noise Regularization for Conditional Density Estimation Jonas Rothfuss Fabio Ferreira S. Boehm Simon Walther Maxim Ulrich Tamim Asfour Andreas Krause 55 32 0 21 Jul 2019
MintNet: Building Invertible Neural Networks with Masked Convolutions Yang Song Chenlin Meng Stefano Ermon 52 68 0 18 Jul 2019