v1v2v3v4v5v6 (latest)

Variational Inference with Normalizing Flows

21 May 2015

Danilo Jimenez Rezende

Papers citing "Variational Inference with Normalizing Flows"

50 / 2,270 papers shown

Title
A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel Yindong Chen Yiwei Wang Lulu Kang Chun Liu 131 2 0 21 Nov 2021
Learn Quasi-stationary Distributions of Finite State Markov Chain Zhiqiang Cai Ling Lin Xiang Zhou BDL OffRL 26 1 0 19 Nov 2021
GFlowNet Foundations Yoshua Bengio Salem Lahlou T. Deleu J. E. Hu Mo Tiwari Emmanuel Bengio 119 241 0 17 Nov 2021
IKFlow: Generating Diverse Inverse Kinematics Solutions Barrett Ames Jeremy Morgan George Konidaris 83 36 0 17 Nov 2021
Normalizing flows for atomic solids Peter Wirnsberger George Papamakarios Borja Ibarz S. Racanière Andy Ballard Alexander Pritzel Charles Blundell 80 41 0 16 Nov 2021
Rethinking Keypoint Representations: Modeling Keypoints and Poses as Objects for Multi-Person Human Pose Estimation William J. McNally Kanav Vats Alexander Wong J. McPhee 103 68 0 16 Nov 2021
ELBD: Efficient score algorithm for feature selection on latent variables of VAE Yiran Dong Chuanhou Gao 47 1 0 15 Nov 2021
Continual Learning via Local Module Composition O. Ostapenko Pau Rodríguez López Massimo Caccia Laurent Charlin KELM CLL 119 67 0 15 Nov 2021
FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows Jiawei Yu1 Ye Zheng Xiang Wang Wei Li Yushuang Wu Rui Zhao Liwei Wu 81 315 0 15 Nov 2021
Learning Neural Models for Continuous-Time Sequences Vinayak Gupta AI4TS 22 1 0 13 Nov 2021
S3RP: Self-Supervised Super-Resolution and Prediction for Advection-Diffusion Process Chulin Wang K. Yeo Xiao Jin Andrés Codas L. Klein Bruce Elmegreen DiffM 82 12 0 08 Nov 2021
NeurInt : Learning to Interpolate through Neural ODEs Avinandan Bose Aniket Das Yatin Dandi P. Rai DiffM DRL 55 0 0 07 Nov 2021
Normalizing Flow as a Flexible Fidelity Objective for Photo-Realistic Super-resolution Andreas Lugmayr Martin Danelljan Feng Yu Luc Van Gool Radu Timofte 57 15 0 05 Nov 2021
Variational Inference with Holder Bounds Junya Chen Danni Lu Zidi Xiu Ke Bai Lawrence Carin Chenyang Tao 54 6 0 04 Nov 2021
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling Greg Ver Steeg Aram Galstyan 80 15 0 03 Nov 2021
A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applications Xinlei Zhou Han Liu Farhad Pourpanah T. Zeng Xizhao Wang UQCV UD 128 61 0 03 Nov 2021
Constructing Neural Network-Based Models for Simulating Dynamical Systems Christian Møldrup Legaard Thomas Schranz G. Schweiger Ján Drgovna Basak Falay C. Gomes Alexandros Iosifidis M. Abkar P. Larsen PINN AI4CE 63 98 0 02 Nov 2021
Uncertainty quantification for ptychography using normalizing flows Agnimitra Dasgupta Z. Di AI4CE 69 5 0 01 Nov 2021
PIE: Pseudo-Invertible Encoder J. Beitler Ivan Sosnovik A. Smeulders 51 10 0 31 Oct 2021
Resampling Base Distributions of Normalizing Flows Vincent Stimper Bernhard Schölkopf José Miguel Hernández-Lobato BDL 96 33 0 29 Oct 2021
Probabilistic Autoencoder using Fisher Information J. Zacherl Philipp Frank T. Ensslin EgoV AI4CE 63 2 0 28 Oct 2021
Validation Methods for Energy Time Series Scenarios from Deep Generative Models Eike Cramer L. R. Gorjão Alexander Mitsos B. Schäfer D. Witthaut Manuel Dahmen 43 16 0 27 Oct 2021
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification Maximilian Stadler Bertrand Charpentier Simon Geisler Daniel Zügner Stephan Günnemann UQCV BDL 120 89 0 26 Oct 2021
Non-Gaussian Gaussian Processes for Few-Shot Regression Marcin Sendera Jacek Tabor A. Nowak Andrzej Bedychaj Massimiliano Patacchiola Tomasz Trzciñski Przemysław Spurek Maciej Ziȩba 92 19 0 26 Oct 2021
Sinusoidal Flow: A Fast Invertible Autoregressive Flow Yumou Wei TPM 43 0 0 26 Oct 2021
A Dynamical System Perspective for Lipschitz Neural Networks Laurent Meunier Blaise Delattre Alexandre Araujo A. Allauzen 130 56 0 25 Oct 2021
Generative Networks for Precision Enthusiasts A. Butter Theo Heimel Sander Hummerich Tobias Krebs Tilman Plehn Armand Rousselot Sophia Vent AI4CE 82 60 0 22 Oct 2021
Learning Stable Vector Fields on Lie Groups Julen Urain Davide Tateo Jan Peters 84 18 0 22 Oct 2021
Generalized Out-of-Distribution Detection: A Survey Jingkang Yang Kaiyang Zhou Yixuan Li Ziwei Liu 311 956 0 21 Oct 2021
Equivariant Finite Normalizing Flows A. Bose Marcus A. Brubaker I. Kobyzev DRL 104 10 0 16 Oct 2021
Learning the Koopman Eigendecomposition: A Diffeomorphic Approach Petar Bevanda Johannes Kirmayr Stefan Sosnowski Sandra Hirche 114 9 0 15 Oct 2021
Function-space Inference with Sparse Implicit Processes Simón Rodríguez Santana B. Zaldívar Daniel Hernández-Lobato 63 12 0 14 Oct 2021
Diffusion Normalizing Flow Qinsheng Zhang Yongxin Chen DiffM 112 94 0 14 Oct 2021
Bundle Networks: Fiber Bundles, Local Trivializations, and a Generative Approach to Exploring Many-to-one Maps Nico Courts Henry Kvinge 40 4 0 13 Oct 2021
Challenges for Unsupervised Anomaly Detection in Particle Physics Katherine Fraser S. Homiller Rashmish K. Mishra B. Ostdiek M. Schwartz DRL 73 45 0 13 Oct 2021
EditVAE: Unsupervised Part-Aware Controllable 3D Point Cloud Shape Generation Shidi Li Miaomiao Liu Christian J. Walder 3DPC 117 29 0 13 Oct 2021
The Deep Generative Decoder: MAP estimation of representations improves modeling of single-cell RNA data Viktoria Schuster A. Krogh 77 4 0 13 Oct 2021
A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful Joeri Hermans Arnaud Delaunoy François Rozet Antoine Wehenkel Volodimir Begy Gilles Louppe 139 43 0 13 Oct 2021
Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling Gianluigi Silvestri Emily Fertig David A. Moore L. Ambrogioni BDL TPM AI4CE 109 4 0 12 Oct 2021
Exchangeability-Aware Sum-Product Networks Stefan Lüdtke Christian Bartelt Heiner Stuckenschmidt TPM 46 3 0 11 Oct 2021
Deep Bayesian inference for seismic imaging with tasks Ali Siahkoohi G. Rizzuti Felix J. Herrmann BDL UQCV 97 21 0 10 Oct 2021
Braxlines: Fast and Interactive Toolkit for RL-driven Behavior Engineering beyond Reward Maximization S. Gu Manfred Diaz Daniel Freeman Hiroki Furuta Seyed Kamyar Seyed Ghasemipour Anton Raichuk Byron David Erik Frey Erwin Coumans Olivier Bachem 82 14 0 10 Oct 2021
An In-depth Summary of Recent Artificial Intelligence Applications in Drug Design Yi Zhang AI4CE 80 6 0 10 Oct 2021
The Neural Testbed: Evaluating Joint Predictions Ian Osband Zheng Wen S. Asghari Vikranth Dwaracherla Botao Hao M. Ibrahimi Dieterich Lawson Xiuyuan Lu Brendan O'Donoghue Benjamin Van Roy UQCV 94 22 0 09 Oct 2021
F-Divergences and Cost Function Locality in Generative Modelling with Quantum Circuits Chiara Leadbeater Louis Sharrock Brian Coyle Marcello Benedetti 59 11 0 08 Oct 2021
PRRS Outbreak Prediction via Deep Switching Auto-Regressive Factorization Modeling M. Shamsabardeh Bahar Azari Beatriz Martínez-López 55 1 0 07 Oct 2021
Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation Dennis Ulmer Christian Hardmeier J. Frellsen BDL UQCV UD EDL PER 150 55 0 06 Oct 2021
Fully Convolutional Cross-Scale-Flows for Image-based Defect Detection Marco Rudolph Tom Wehrbein Bodo Rosenhahn Bastian Wandt UQCV 140 222 0 06 Oct 2021
Knothe-Rosenblatt transport for Unsupervised Domain Adaptation Aladin Virmaux Illyyne Saffar Jianfeng Zhang Balázs Kégl OOD 41 0 0 06 Oct 2021
DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulation Gwanghyun Kim Taesung Kwon Jong Chul Ye DiffM 247 657 0 06 Oct 2021