Flows for simultaneous manifold learning and density estimation

31 March 2020

Papers citing "Flows for simultaneous manifold learning and density estimation"

33 / 33 papers shown

Title
Accurate Forgetting for Heterogeneous Federated Continual Learning Abudukelimu Wuerkaixi Sen Cui J. Zhang Kunda Yan Bo Han Gang Niu Lei Fang Changshui Zhang Masashi Sugiyama 106 8 0 20 Feb 2025
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models Daniela de Albuquerque John Pearson DiffM 51 0 0 03 Jan 2025
Analyzing Generative Models by Manifold Entropic Metrics Daniel Galperin Ullrich Köthe DRL 16 0 0 25 Oct 2024
Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax I. Butakov Alexander Sememenko Alexander Tolmachev Andrey Gladkov Marina Munkhoeva Alexey Frolov 27 0 0 09 Oct 2024
Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups Yuchen Zhu Tianrong Chen Lingkai Kong Evangelos A. Theodorou Molei Tao DiffM 35 3 0 25 May 2024
On Kernel-based Variational Autoencoder Tian Qin Wei-Min Huang DRL BDL 58 1 0 21 May 2024
Unified framework for diffusion generative models in SO(3): applications in computer vision and astrophysics Yesukhei Jagvaral F. Lanusse Rachel Mandelbaum DiffM 22 5 0 18 Dec 2023
Multivariate Scenario Generation of Day-Ahead Electricity Prices using Normalizing Flows Hannes Hilger D. Witthaut Manuel Dahmen L. R. Gorjão Julius Trebbien Eike Cramer 23 5 0 23 Nov 2023
Canonical normalizing flows for manifold learning Kyriakos Flouris E. Konukoglu DRL 46 7 0 19 Oct 2023
Implicit Variational Inference for High-Dimensional Posteriors Anshuk Uppal Kristoffer Stensbo-Smidt Wouter Boomsma J. Frellsen BDL 10 1 0 10 Oct 2023
On Explicit Curvature Regularization in Deep Generative Models Yonghyeon Lee Frank C. Park BDL 22 12 0 19 Sep 2023
Out-of-distribution detection using normalizing flows on the data manifold S. Razavi M. Mehmanchi Reshad Hosseini Mostafa Tavassolipour OODD 35 0 0 26 Aug 2023
A Review of Change of Variable Formulas for Generative Modeling Ullrich Kothe 13 6 0 04 Aug 2023
Explicitly Minimizing the Blur Error of Variational Autoencoders G. Bredell Kyriakos Flouris K. Chaitanya Ertunc Erdil E. Konukoglu 11 22 0 12 Apr 2023
Injectivity of ReLU networks: perspectives from statistical physics Antoine Maillard Afonso S. Bandeira David Belius Ivan Dokmanić S. Nakajima 23 4 0 27 Feb 2023
Deep Injective Prior for Inverse Scattering AmirEhsan Khorashadizadeh Vahid Khorashadi-Zadeh Sepehr Eskandari Guy A. E. Vandenbosch Ivan Dokmanić 13 6 0 08 Jan 2023
Effects of Data Geometry in Early Deep Learning Saket Tiwari G. Konidaris 59 7 0 29 Dec 2022
LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood Piotr Tempczyk Rafał Michaluk Łukasz Garncarek Przemysław Spurek Jacek Tabor Adam Goliñski 33 26 0 29 Jun 2022
Flowification: Everything is a Normalizing Flow Bálint Máté Samuel Klein T. Golling Franccois Fleuret 8 3 0 30 May 2022
COMET Flows: Towards Generative Modeling of Multivariate Extremes and Tail Dependence Andrew McDonald Pang-Ning Tan Lifeng Luo 21 9 0 02 May 2022
Conditional Injective Flows for Bayesian Imaging AmirEhsan Khorashadizadeh K. Kothari Leonardo Salsi Ali Aghababaei Harandi Maarten V. de Hoop Ivan Dokmanić MedIm 16 16 0 15 Apr 2022
Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance S. Tsan Raghav Kansal Anthony Aportela Daniel Madrigal Diaz Javier Mauricio Duarte S. Krishna Farouk Mokhtar J. Vlimant M. Pierini 14 19 0 24 Nov 2021
Riemannian Convex Potential Maps Samuel N. Cohen Brandon Amos Y. Lipman 13 22 0 18 Jun 2021
Latent Space Refinement for Deep Generative Models R. Winterhalder Marco Bellagente Benjamin Nachman BDL GAN DRL DiffM 8 27 0 01 Jun 2021
Principal Component Density Estimation for Scenario Generation Using Normalizing Flows Eike Cramer Alexander Mitsos Raúl Tempone Manuel Dahmen 24 13 0 21 Apr 2021
Trumpets: Injective Flows for Inference and Inverse Problems K. Kothari AmirEhsan Khorashadizadeh Maarten V. de Hoop Ivan Dokmanić TPM 20 50 0 20 Feb 2021
E Pluribus Unum Ex Machina: Learning from Many Collider Events at Once Benjamin Nachman Jesse Thaler 16 33 0 18 Jan 2021
Flow-based Generative Models for Learning Manifold to Manifold Mappings Xingjian Zhen Rudrasis Chakraborty Liu Yang Vikas Singh DRL MedIm 16 9 0 18 Dec 2020
Principled Interpolation in Normalizing Flows Samuel G. Fadel Sebastian Mair Ricardo da S. Torres Ulf Brefeld 67 3 0 22 Oct 2020
Neural Manifold Ordinary Differential Equations Aaron Lou Derek Lim Isay Katsman Leo Huang Qingxuan Jiang Ser-Nam Lim Christopher De Sa BDL AI4CE 8 78 0 18 Jun 2020
Ordering Dimensions with Nested Dropout Normalizing Flows Artur Bekasov Iain Murray DRL 15 5 0 15 Jun 2020
Probabilistic Autoencoder Vanessa Böhm U. Seljak UQCV BDL DRL 8 32 0 09 Jun 2020
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 262 10,320 0 12 Dec 2018