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Variational Inference with Normalizing Flows

21 May 2015

Danilo Jimenez Rezende

Papers citing "Variational Inference with Normalizing Flows"

50 / 2,268 papers shown

Title
Learning Bijective Feature Maps for Linear ICA A. Camuto M. Willetts Brooks Paige Chris Holmes Stephen J. Roberts 46 3 0 18 Feb 2020
Gravitational-wave parameter estimation with autoregressive neural network flows Stephen R. Green C. Simpson J. Gair BDL 130 86 0 18 Feb 2020
Deep Gaussian Markov Random Fields Per Sidén Fredrik Lindsten BDL 59 22 0 18 Feb 2020
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models Chin-Wei Huang Laurent Dinh Aaron Courville DRL 115 89 0 17 Feb 2020
Learning Robust Representations via Multi-View Information Bottleneck Marco Federici Anjan Dutta Patrick Forré Nate Kushman Zeynep Akata SLR 83 260 0 17 Feb 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 156 186 0 16 Feb 2020
The Phantom Steering Effect in Q&A Websites Nicholas Hoernle Gregory Kehne Ariel D. Procaccia Y. Gal LLMSV 13 2 0 14 Feb 2020
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees Jonas Rothfuss Vincent Fortuin Martin Josifoski Andreas Krause UQCV 93 127 0 13 Feb 2020
Black-Box Optimization with Local Generative Surrogates S. Shirobokov V. Belavin Michael Kagan Andrey Ustyuzhanin A. G. Baydin 44 3 0 11 Feb 2020
Learning Stochastic Behaviour from Aggregate Data Shaojun Ma Shu Liu H. Zha Haomin Zhou 144 15 0 10 Feb 2020
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics Alexander Tong Jessie Huang Guy Wolf David van Dijk Smita Krishnaswamy 77 177 0 09 Feb 2020
Learning Implicit Generative Models with Theoretical Guarantees Yuan Gao Jian Huang Yuling Jiao Jin Liu 66 7 0 07 Feb 2020
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks J. Swiatkowski Kevin Roth Bastiaan S. Veeling Linh-Tam Tran Joshua V. Dillon Jasper Snoek Stephan Mandt Tim Salimans Rodolphe Jenatton Sebastian Nowozin BDL 89 47 0 07 Feb 2020
Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow Didrik Nielsen Ole Winther MQ 235 13 0 06 Feb 2020
Normalizing Flows on Tori and Spheres Danilo Jimenez Rezende George Papamakarios S. Racanière M. S. Albergo G. Kanwar P. Shanahan Kyle Cranmer TPM 93 157 0 06 Feb 2020
Learning Extremal Representations with Deep Archetypal Analysis S. Keller M. Samarin Fabricio Arend Torres Mario Wieser Volker Roth 78 24 0 03 Feb 2020
Automatic structured variational inference L. Ambrogioni Kate Lin Emily Fertig Sharad Vikram Max Hinne Dave Moore Marcel van Gerven BDL 84 31 0 03 Feb 2020
Variational Item Response Theory: Fast, Accurate, and Expressive Mike Wu R. Davis B. Domingue Chris Piech Noah D. Goodman OffRL 107 55 0 01 Feb 2020
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation Chence Shi Minkai Xu Zhaocheng Zhu Weinan Zhang Ming Zhang Jian Tang 237 439 0 26 Jan 2020
Safe Robot Navigation via Multi-Modal Anomaly Detection Lorenz Wellhausen René Ranftl Marco Hutter 87 77 0 22 Jan 2020
A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor Analysis Christopher J. Urban Daniel J. Bauer BDL 81 33 0 22 Jan 2020
i-flow: High-dimensional Integration and Sampling with Normalizing Flows Christina Gao J. Isaacson Claudius Krause AI4CE 83 111 0 15 Jan 2020
Invertible Generative Modeling using Linear Rational Splines H. M. Dolatabadi S. Erfani C. Leckie 127 65 0 15 Jan 2020
Anomaly Detection with Density Estimation Benjamin Nachman David Shih 74 220 0 14 Jan 2020
Information Newton's flow: second-order optimization method in probability space Yifei Wang Wuchen Li 111 31 0 13 Jan 2020
Learning Generative Models using Denoising Density Estimators Siavash Bigdeli Geng Lin Tiziano Portenier L. A. Dunbar Matthias Zwicker DiffM 106 16 0 08 Jan 2020
A Probability Density Theory for Spin-Glass Systems Gavin Hartnett Masoud Mohseni 68 3 0 03 Jan 2020
Discrete and Continuous Action Representation for Practical RL in Video Games Olivier Delalleau Maxim Peter Eloi Alonso Adrien Logut 81 53 0 23 Dec 2019
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse Bin Dai Ziyu Wang David Wipf DRL 97 76 0 23 Dec 2019
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing V. Monga Yuelong Li Yonina C. Eldar 130 1,027 0 22 Dec 2019
Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax Andres Potapczynski Gabriel Loaiza-Ganem John P. Cunningham 109 30 0 19 Dec 2019
C-Flow: Conditional Generative Flow Models for Images and 3D Point Clouds Albert Pumarola S. Popov Francesc Moreno-Noguer V. Ferrari 3DPC AI4CE 156 80 0 15 Dec 2019
Bayesian Variational Autoencoders for Unsupervised Out-of-Distribution Detection Erik A. Daxberger José Miguel Hernández-Lobato UQCV 103 63 0 11 Dec 2019
Multimodal Generative Models for Compositional Representation Learning Mike Wu Noah D. Goodman GAN DRL 97 17 0 11 Dec 2019
InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers T. Nguyen Animesh Garg Richard G. Baraniuk Anima Anandkumar TPM 111 9 0 09 Dec 2019
Efficient Black-box Assessment of Autonomous Vehicle Safety J. Norden Matthew O'Kelly Aman Sinha 89 66 0 08 Dec 2019
Neural Networks with Cheap Differential Operators Ricky T. Q. Chen David Duvenaud 67 35 0 08 Dec 2019
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 219 1,724 0 05 Dec 2019
Learning Multi-layer Latent Variable Model via Variational Optimization of Short Run MCMC for Approximate Inference Erik Nijkamp Bo Pang Tian Han Linqi Zhou Song-Chun Zhu Ying Nian Wu BDL DRL 89 2 0 04 Dec 2019
A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems Lars Ruthotto Stanley Osher Wuchen Li L. Nurbekyan Samy Wu Fung AI4CE 178 220 0 04 Dec 2019
WaveFlow: A Compact Flow-based Model for Raw Audio Ming-Yu Liu Kainan Peng Kexin Zhao Z. Song 102 117 0 03 Dec 2019
Flow Contrastive Estimation of Energy-Based Models Ruiqi Gao Erik Nijkamp Diederik P. Kingma Zhen Xu Andrew M. Dai Ying Nian Wu GAN 101 115 0 02 Dec 2019
Learning Likelihoods with Conditional Normalizing Flows Christina Winkler Daniel E. Worrall Emiel Hoogeboom Max Welling TPM 296 227 0 29 Nov 2019
Self-attention with Functional Time Representation Learning Da Xu Chuanwei Ruan Sushant Kumar Evren Körpeoglu Kannan Achan AI4TS 82 118 0 28 Nov 2019
Mixed-curvature Variational Autoencoders Ondrej Skopek O. Ganea Gary Bécigneul CML DRL BDL 76 102 0 19 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 92 8 0 11 Nov 2019
Machine learning for molecular simulation Frank Noé A. Tkatchenko K. Müller C. Clementi AI4CE 90 668 0 07 Nov 2019
Statistical Inference in Mean-Field Variational Bayes Wei Han Yun Yang 48 18 0 04 Nov 2019
The frontier of simulation-based inference Kyle Cranmer Johann Brehmer Gilles Louppe AI4CE 271 857 0 04 Nov 2019
Convolutional Conditional Neural Processes Jonathan Gordon W. Bruinsma Andrew Y. K. Foong James Requeima Yann Dubois Richard Turner BDL 94 168 0 29 Oct 2019