Normalizing Flows for Probabilistic Modeling and Inference

v1v2 (latest)

Normalizing Flows for Probabilistic Modeling and Inference

Journal of machine learning research (JMLR), 2019

5 December 2019

George Papamakarios

Eric T. Nalisnick

Danilo Jimenez Rezende

Balaji Lakshminarayanan

ArXiv (abs)PDF HTML

Papers citing "Normalizing Flows for Probabilistic Modeling and Inference"

10 / 1,110 papers shown

Title
Kullback-Leibler Divergence-Based Out-of-Distribution Detection with Flow-Based Generative ModelsIEEE Transactions on Knowledge and Data Engineering (TKDE), 2020 Yufeng Zhang Jia Pan Wanwei Liu Zhenbang Chen Jing Wang Zhiming Liu KenLi Li H. Wei OODD DRL 380 6 0 09 Feb 2020
Normalizing Flows on Tori and SpheresInternational Conference on Machine Learning (ICML), 2020 Danilo Jimenez Rezende George Papamakarios S. Racanière M. S. Albergo G. Kanwar P. Shanahan Kyle Cranmer TPM 246 171 0 06 Feb 2020
i-flow: High-dimensional Integration and Sampling with Normalizing Flows Christina Gao J. Isaacson Claudius Krause AI4CE 207 124 0 15 Jan 2020
Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGOIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019 Pablo Morales-Álvarez Pablo Ruiz S. Coughlin Rafael Molina Aggelos K. Katsaggelos 162 16 0 05 Nov 2019
Distilling Importance Sampling for Likelihood Free InferenceJournal of Computational And Graphical Statistics (JCGS), 2019 D. Prangle Cecilia Viscardi 301 5 0 08 Oct 2019
The Neural Moving Average Model for Scalable Variational Inference of State Space ModelsConference on Uncertainty in Artificial Intelligence (UAI), 2019 Tom Ryder D. Prangle Andrew Golightly Isaac Matthews BDL AI4TS 292 8 0 02 Oct 2019
Neural Canonical Transformation with Symplectic FlowsPhysical Review X (PRX), 2019 Shuo-Hui Li Chen Dong Linfeng Zhang Lei Wang DRL 400 29 0 30 Sep 2019
Validation of Approximate Likelihood and Emulator Models for Computationally Intensive SimulationsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Niccolò Dalmasso Ann B. Lee Rafael Izbicki T. Pospisil Ilmun Kim Chieh-An Lin 182 9 0 27 May 2019
HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian InferenceAAAI Conference on Artificial Intelligence (AAAI), 2019 Jakob Kruse Gianluca Detommaso Ullrich Kothe Robert Scheichl 255 47 0 25 May 2019
MoGlow: Probabilistic and controllable motion synthesis using normalising flowsACM Transactions on Graphics (TOG), 2019 G. Henter Simon Alexanderson Jonas Beskow 270 102 0 16 May 2019