Variational Inference with Normalizing Flows

21 May 2015

Danilo Jimenez Rezende

Papers citing "Variational Inference with Normalizing Flows"

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Title
Efficient Semi-Implicit Variational Inference Vincent Moens Hang Ren A. Maraval Rasul Tutunov Jun Wang H. Ammar 85 6 0 15 Jan 2021
Benchmarking Simulation-Based Inference Jan-Matthis Lueckmann Jan Boelts David S. Greenberg P. J. Gonçalves Jakob H. Macke 104 186 0 12 Jan 2021
Preconditioned training of normalizing flows for variational inference in inverse problems Ali Siahkoohi G. Rizzuti M. Louboutin Philipp A. Witte Felix J. Herrmann 75 32 0 11 Jan 2021
How to Train Your Energy-Based Models Yang Song Diederik P. Kingma DiffM 24 243 0 09 Jan 2021
Variational Determinant Estimation with Spherical Normalizing Flows Simon Passenheim Emiel Hoogeboom BDL 31 1 0 24 Dec 2020
Flow-based Generative Models for Learning Manifold to Manifold Mappings Xingjian Zhen Rudrasis Chakraborty Liu Yang Vikas Singh DRL MedIm 31 9 0 18 Dec 2020
Model-Based Deep Learning Nir Shlezinger Jay Whang Yonina C. Eldar A. Dimakis 33 318 0 15 Dec 2020
Calibrated Adaptive Probabilistic ODE Solvers Nathanael Bosch Philipp Hennig Filip Tronarp 41 29 0 15 Dec 2020
A case for new neural network smoothness constraints Mihaela Rosca T. Weber Arthur Gretton S. Mohamed AAML 35 48 0 14 Dec 2020
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization Chin-Wei Huang Ricky T. Q. Chen Christos Tsirigotis Aaron Courville OT 119 96 0 10 Dec 2020
HEBO Pushing The Limits of Sample-Efficient Hyperparameter Optimisation Alexander I. Cowen-Rivers Wenlong Lyu Rasul Tutunov Zhi Wang Antoine Grosnit ... A. Maraval Hao Jianye Jun Wang Jan Peters H. Ammar 27 74 0 07 Dec 2020
ChartPointFlow for Topology-Aware 3D Point Cloud Generation Takumi Kimura Takashi Matsubara K. Uehara 3DPC 31 8 0 04 Dec 2020
Generative Layout Modeling using Constraint Graphs W. Para Paul Guerrero Tom Kelly Leonidas J. Guibas Peter Wonka 31 69 0 26 Nov 2020
Regularization with Latent Space Virtual Adversarial Training Genki Osada Budrul Ahsan Revoti Prasad Bora Takashi Nishide 30 14 0 26 Nov 2020
Variational Monocular Depth Estimation for Reliability Prediction Noriaki Hirose S. Taguchi Keisuke Kawano Satoshi Koide MDE 34 4 0 24 Nov 2020
Solving high-dimensional parameter inference: marginal posterior densities & Moment Networks N. Jeffrey Benjamin Dan Wandelt 22 38 0 11 Nov 2020
Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference M. Vandegar Michael Kagan Antoine Wehenkel Gilles Louppe 34 27 0 11 Nov 2020
Wave-Tacotron: Spectrogram-free end-to-end text-to-speech synthesis Ron J. Weiss RJ Skerry-Ryan Eric Battenberg Soroosh Mariooryad Diederik P. Kingma 24 98 0 06 Nov 2020
Causal Autoregressive Flows Ilyes Khemakhem R. Monti R. Leech Aapo Hyvarinen CML OOD AI4CE 27 108 0 04 Nov 2020
Transforming Gaussian Processes With Normalizing Flows Juan Maroñas Oliver Hamelijnck Jeremias Knoblauch Theodoros Damoulas 36 34 0 03 Nov 2020
Generative Temporal Difference Learning for Infinite-Horizon Prediction Michael Janner Igor Mordatch Sergey Levine AI4CE 20 34 0 27 Oct 2020
Deep Probabilistic Imaging: Uncertainty Quantification and Multi-modal Solution Characterization for Computational Imaging He Sun Katherine Bouman UQCV 25 74 0 27 Oct 2020
Reducing the Computational Cost of Deep Generative Models with Binary Neural Networks Thomas Bird F. Kingma David Barber SyDa MQ AI4CE 26 9 0 26 Oct 2020
Scalable Gaussian Process Variational Autoencoders Metod Jazbec Matthew Ashman Vincent Fortuin Michael Pearce Stephan Mandt Gunnar Rätsch DRL BDL 26 25 0 26 Oct 2020
ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows Julen Urain M. Ginesi Davide Tateo Jan Peters AI4CE 21 57 0 25 Oct 2020
Variational Bayesian Unlearning Q. Nguyen Bryan Kian Hsiang Low Patrick Jaillet BDL MU 27 122 0 24 Oct 2020
Geometry-Aware Hamiltonian Variational Auto-Encoder Clément Chadebec Clément Mantoux S. Allassonnière DRL 24 15 0 22 Oct 2020
NU-GAN: High resolution neural upsampling with GAN Rithesh Kumar Kundan Kumar Vicki Anand Yoshua Bengio Aaron Courville 27 25 0 22 Oct 2020
Principled Interpolation in Normalizing Flows Samuel G. Fadel Sebastian Mair Ricardo da S. Torres Ulf Brefeld 83 3 0 22 Oct 2020
Semi-parametric $γ$ -ray modeling with Gaussian processes and variational inference S. Mishra-Sharma Kyle Cranmer MedIm 21 7 0 20 Oct 2020
Probabilistic Character Motion Synthesis using a Hierarchical Deep Latent Variable Model Saeed Ghorbani C. Wloka Ali Etemad M. Brubaker N. Troje 3DV 41 31 0 20 Oct 2020
Hierarchical Autoregressive Modeling for Neural Video Compression Ruihan Yang Yibo Yang Joseph Marino Stephan Mandt BDL VGen 112 46 0 19 Oct 2020
Orbital MCMC Kirill Neklyudov Max Welling 39 7 0 15 Oct 2020
Symbolic Parallel Adaptive Importance Sampling for Probabilistic Program Analysis Yicheng Luo A. Filieri Yuanshuo Zhou 19 5 0 10 Oct 2020
Information Theory Measures via Multidimensional Gaussianization Valero Laparra J. E. Johnson Gustau Camps-Valls Raúl Santos-Rodríguez Jesús Malo 38 11 0 08 Oct 2020
Representing Point Clouds with Generative Conditional Invertible Flow Networks Michal Stypulkowski Kacper Kania M. Zamorski Maciej Ziȩba Tomasz Trzciñski J. Chorowski 3DPC 31 4 0 07 Oct 2020
Improving Sequential Latent Variable Models with Autoregressive Flows Joseph Marino Lei Chen Jiawei He Stephan Mandt BDL AI4TS 30 12 0 07 Oct 2020
Denoising Diffusion Implicit Models Jiaming Song Chenlin Meng Stefano Ermon VLM DiffM 56 7,024 0 06 Oct 2020
Learning Variational Word Masks to Improve the Interpretability of Neural Text Classifiers Hanjie Chen Yangfeng Ji AAML VLM 17 63 0 01 Oct 2020
Variational Disentanglement for Rare Event Modeling Zidi Xiu Chenyang Tao M. Gao Connor Davis B. Goldstein Ricardo Henao CML DRL 32 6 0 17 Sep 2020
Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals Saloni Dash V. Balasubramanian Amit Sharma CML 27 65 0 17 Sep 2020
Multilinear Latent Conditioning for Generating Unseen Attribute Combinations Markos Georgopoulos Grigorios G. Chrysos Maja Pantic Yannis Panagakis GAN DRL 24 17 0 09 Sep 2020
Quasi-symplectic Langevin Variational Autoencoder Zihao Wang H. Delingette BDL DRL 15 4 0 02 Sep 2020
Low-rank Characteristic Tensor Density Estimation Part I: Foundations Magda Amiridi Nikos Kargas N. Sidiropoulos 19 19 0 27 Aug 2020
Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems Aman Sinha Matthew O'Kelly Russ Tedrake John C. Duchi 44 48 0 24 Aug 2020
TNT: Target-driveN Trajectory Prediction Hang Zhao Jiyang Gao Tian-Shing Lan Chen Sun Benjamin Sapp ... Yi Shen Yuning Chai Cordelia Schmid Congcong Li Dragomir Anguelov 57 537 0 19 Aug 2020
Audio Dequantization for High Fidelity Audio Generation in Flow-based Neural Vocoder Hyun-Wook Yoon Sang-Hoon Lee Hyeong-Rae Noh Seong-Whan Lee 20 11 0 16 Aug 2020
Learning Gradient Fields for Shape Generation Ruojin Cai Guandao Yang Hadar Averbuch-Elor Jinwei Gu Serge J. Belongie Noah Snavely B. Hariharan 3DPC 19 280 0 14 Aug 2020
Generative Adversarial Networks for Image and Video Synthesis: Algorithms and Applications Xuan Li Xun Huang Jiahui Yu Ting-Chun Wang Arun Mallya GAN 30 153 0 06 Aug 2020
Geometrically Enriched Latent Spaces Georgios Arvanitidis Søren Hauberg Bernhard Schölkopf DRL 19 51 0 02 Aug 2020