Normalizing Flows for Probabilistic Modeling and Inference

5 December 2019

George Papamakarios

Eric T. Nalisnick

Danilo Jimenez Rezende

S. Mohamed

Balaji Lakshminarayanan

TPM

AI4CE

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Papers citing "Normalizing Flows for Probabilistic Modeling and Inference"

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PaCMO: Partner Dependent Human Motion Generation in Dyadic Human Activity using Neural Operators Md Ashiqur Rahman Jasorsi Ghosh Hrishikesh Viswanath Kamyar Azizzadenesheli Aniket Bera 27 8 0 25 Nov 2022
Validation Diagnostics for SBI algorithms based on Normalizing Flows J. Linhart Alexandre Gramfort P. L. C. R. M. -. Inria 41 7 0 17 Nov 2022
Normalizing Flows for Hierarchical Bayesian Analysis: A Gravitational Wave Population Study David Ruhe Kaze W. K. Wong M. Cranmer Patrick Forré 16 6 0 15 Nov 2022
Diffusion Models for Medical Image Analysis: A Comprehensive Survey A. Kazerouni Ehsan Khodapanah Aghdam Moein Heidari Reza Azad Mohsen Fayyaz I. Hacihaliloglu Dorit Merhof DiffM MedIm 49 358 0 14 Nov 2022
Aspects of scaling and scalability for flow-based sampling of lattice QCD Ryan Abbott M. S. Albergo Aleksandar Botev D. Boyda Kyle Cranmer ... Ali Razavi Danilo Jimenez Rezende F. Romero-López P. Shanahan Julian M. Urban 32 33 0 14 Nov 2022
OverFlow: Putting flows on top of neural transducers for better TTS Shivam Mehta Ambika Kirkland Harm Lameris Jonas Beskow Éva Székely G. Henter AI4TS 39 12 0 13 Nov 2022
Learning Riemannian Stable Dynamical Systems via Diffeomorphisms Jiechao Zhang Hadi Beik-Mohammadi Leonel Rozo 25 15 0 06 Nov 2022
Flows for Flows: Training Normalizing Flows Between Arbitrary Distributions with Maximum Likelihood Estimation Samuel Klein J. A. Raine T. Golling TPM 28 10 0 04 Nov 2022
An optimal control perspective on diffusion-based generative modeling Julius Berner Lorenz Richter Karen Ullrich DiffM 30 80 0 02 Nov 2022
AltUB: Alternating Training Method to Update Base Distribution of Normalizing Flow for Anomaly Detection Yeongmin Kim Huiwon Jang Dongkeon Lee Ho-Jin Choi 35 9 0 26 Oct 2022
Whitening Convergence Rate of Coupling-based Normalizing Flows Felix Dräxler Christoph Schnörr Ullrich Kothe 36 7 0 25 Oct 2022
Optimization for Amortized Inverse Problems Tianci Liu Tong Yang Quan Zhang Qi Lei 36 5 0 25 Oct 2022
Transport Reversible Jump Proposals L. Davies Roberto Salomone Matthew Sutton Christopher C. Drovandi BDL 27 1 0 22 Oct 2022
Improved Normalizing Flow-Based Speech Enhancement using an All-pole Gammatone Filterbank for Conditional Input Representation Martin Strauss Matteo Torcoli B. Edler 21 4 0 21 Oct 2022
TTTFlow: Unsupervised Test-Time Training with Normalizing Flow David Osowiechi G. A. V. Hakim Mehrdad Noori Milad Cheraghalikhani Ismail Ben Ayed Christian Desrosiers OOD 27 22 0 20 Oct 2022
Sampling using Adaptive Regenerative Processes Hector McKimm Andi Q. Wang M. Pollock Christian P. Robert Gareth O. Roberts 21 1 0 18 Oct 2022
Transfer learning with affine model transformation Shunya Minami Kenji Fukumizu Yoshihiro Hayashi Ryo Yoshida 27 1 0 18 Oct 2022
Blind Super-Resolution for Remote Sensing Images via Conditional Stochastic Normalizing Flows Hanlin Wu Ning Ni Shan Wang Li-bao Zhang 38 8 0 14 Oct 2022
Modular Flows: Differential Molecular Generation Yogesh Verma Samuel Kaski Markus Heinonen Vikas K. Garg 29 14 0 12 Oct 2022
Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models Louis Sharrock J. Simons Song Liu Mark Beaumont DiffM 64 34 0 10 Oct 2022
Connecting Surrogate Safety Measures to Crash Probablity via Causal Probabilistic Time Series Prediction Jiajian Lu Offer Grembek M. Hansen AI4TS 21 0 0 04 Oct 2022
Training Normalizing Flows from Dependent Data Matthias Kirchler C. Lippert Marius Kloft TPM 24 2 0 29 Sep 2022
Local_INN: Implicit Map Representation and Localization with Invertible Neural Networks Zirui Zang Hongrui Zheng Johannes Betz Rahul Mangharam 40 6 0 24 Sep 2022
Turning Normalizing Flows into Monge Maps with Geodesic Gaussian Preserving Flows G. Morel Lucas Drumetz Simon Benaïchouche Nicolas Courty F. Rousseau OT 30 6 0 22 Sep 2022
Sample-based Uncertainty Quantification with a Single Deterministic Neural Network T. Kanazawa Chetan Gupta UQCV 30 4 0 17 Sep 2022
Asymptotic Statistical Analysis of $f$ -divergence GAN Xinwei Shen Kani Chen Tong Zhang 21 2 0 14 Sep 2022
Deep Variational Free Energy Approach to Dense Hydrogen H.-j. Xie Ziqun Li Han Wang Linfeng Zhang Lei Wang 35 9 0 13 Sep 2022
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow Xingchao Liu Chengyue Gong Qiang Liu OOD 55 850 0 07 Sep 2022
Investigating the Impact of Model Misspecification in Neural Simulation-based Inference Patrick W Cannon Daniel Ward Sebastian M. Schmon 25 34 0 05 Sep 2022
Conditional Independence Testing via Latent Representation Learning Bao Duong T. Nguyen BDL CML 31 6 0 04 Sep 2022
Diffusion Models: A Comprehensive Survey of Methods and Applications Ling Yang Zhilong Zhang Yingxia Shao Shenda Hong Runsheng Xu Yue Zhao Wentao Zhang Bin Cui Ming-Hsuan Yang DiffM MedIm 224 1,311 0 02 Sep 2022
Tackling Multimodal Device Distributions in Inverse Photonic Design using Invertible Neural Networks Michel Frising J. Bravo-Abad F. Prins 27 2 0 29 Aug 2022
Uncovering dark matter density profiles in dwarf galaxies with graph neural networks Tri Nguyen S. Mishra-Sharma R. Williams L. Necib 18 2 0 26 Aug 2022
Deep Structural Causal Shape Models Rajat Rasal Daniel Coelho De Castro Nick Pawlowski Ben Glocker 3DV MedIm 33 12 0 23 Aug 2022
Neural PCA for Flow-Based Representation Learning Shen Li Bryan Hooi DRL 13 1 0 23 Aug 2022
HSIC-InfoGAN: Learning Unsupervised Disentangled Representations by Maximising Approximated Mutual Information Xiao Liu Spyridon Thermos Pedro Sanchez Alison Q. OÑeil Sotirios A. Tsaftaris 39 1 0 06 Aug 2022
Interpretable Uncertainty Quantification in AI for HEP Thomas Y. Chen B. Dey A. Ghosh Michael Kagan Brian D. Nord Nesar Ramachandra 33 7 0 05 Aug 2022
Graph neural networks for materials science and chemistry Patrick Reiser Marlen Neubert André Eberhard Luca Torresi Chen Zhou ... Houssam Metni Clint van Hoesel Henrik Schopmans T. Sommer Pascal Friederich GNN AI4CE 50 373 0 05 Aug 2022
An Optimal Likelihood Free Method for Biological Model Selection Vincent D. Zaballa E. Hui 34 0 0 03 Aug 2022
Flow Annealed Importance Sampling Bootstrap Laurence Illing Midgley Vincent Stimper G. Simm Bernhard Schölkopf José Miguel Hernández-Lobato 38 77 0 03 Aug 2022
Non-Uniform Diffusion Models Georgios Batzolis Jan Stanczuk Carola-Bibiane Schönlieb Christian Etmann DiffM 20 15 0 20 Jul 2022
Differentiable Agent-based Epidemiology Ayush Chopra Alexander Rodríguez J. Subramanian Arnau Quera-Bofarull Balaji Krishnamurthy B. Prakash Ramesh Raskar AI4CE 25 19 0 20 Jul 2022
Stable Invariant Models via Koopman Spectra Takuya Konishi Yoshinobu Kawahara 23 3 0 15 Jul 2022
Text to Image Synthesis using Stacked Conditional Variational Autoencoders and Conditional Generative Adversarial Networks Haileleol Tibebu Aadin Malik V. D. Silva GAN 20 7 0 06 Jul 2022
Learning Optimal Transport Between two Empirical Distributions with Normalizing Flows Florentin Coeurdoux N. Dobigeon P. Chainais OOD OT 32 7 0 04 Jul 2022
Uncertainty Quantification for Deep Unrolling-Based Computational Imaging Canberk Ekmekci Müjdat Çetin UQCV 19 12 0 02 Jul 2022
Multi-Objective Coordination Graphs for the Expected Scalarised Returns with Generative Flow Models Conor F. Hayes T. Verstraeten D. Roijers Enda Howley Patrick Mannion 24 3 0 01 Jul 2022
Learning Optimal Flows for Non-Equilibrium Importance Sampling Yu Cao Eric Vanden-Eijnden 21 3 0 20 Jun 2022
Spherical Sliced-Wasserstein Clément Bonet P. Berg Nicolas Courty Françcois Septier Lucas Drumetz Minh Pham 30 27 0 17 Jun 2022
PAVI: Plate-Amortized Variational Inference Louis Rouillard Thomas Moreau Demian Wassermann 25 1 0 10 Jun 2022