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Flows for simultaneous manifold learning and density estimation
v1v2v3 (latest)

Flows for simultaneous manifold learning and density estimation

Neural Information Processing Systems (NeurIPS), 2020
31 March 2020
Johann Brehmer
Kyle Cranmer
    DRLAI4CE
ArXiv (abs)PDFHTML

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

50 / 114 papers shown
Split-Flows: Measure Transport and Information Loss Across Molecular Resolutions
Split-Flows: Measure Transport and Information Loss Across Molecular Resolutions
Sander Hummerich
Tristan Bereau
Ullrich Kothe
147
2
0
03 Nov 2025
Marginal Flow: a flexible and efficient framework for density estimation
Marginal Flow: a flexible and efficient framework for density estimation
M. Negri
Jonathan Aellen
Manuel Jahn
AmirEhsan Khorashadizadeh
Volker Roth
147
0
0
30 Sep 2025
Misspecification-robust amortised simulation-based inference using variational methods
Misspecification-robust amortised simulation-based inference using variational methods
Matthew O'Callaghan
Kaisey S. Mandel
Gerry Gilmore
175
0
0
06 Sep 2025
On Convolutions, Intrinsic Dimension, and Diffusion Models
On Convolutions, Intrinsic Dimension, and Diffusion Models
Kin Kwan Leung
Rasa Hosseinzadeh
Gabriel Loaiza-Ganem
DiffM
192
0
0
25 Jun 2025
Offline RL with Smooth OOD Generalization in Convex Hull and its NeighborhoodInternational Conference on Learning Representations (ICLR), 2025
Qingmao Yao
Zhichao Lei
Tianyuan Chen
Ziyue Yuan
Xuefan Chen
Jianxiang Liu
Faguo Wu
Xiao Zhang
OffRL
245
2
0
10 Jun 2025
Sparse Autoencoders, Again?
Sparse Autoencoders, Again?
Yin Lu
X. Zhu
Tong He
David Wipf
351
1
0
05 Jun 2025
Beyond Diagonal Covariance: Flexible Posterior VAEs via Free-Form Injective Flows
Beyond Diagonal Covariance: Flexible Posterior VAEs via Free-Form Injective Flows
Peter Sorrenson
Lukas Lührs
Hans Olischläger
Ullrich Kothe
193
1
0
02 Jun 2025
Learning geometry and topology via multi-chart flows
Learning geometry and topology via multi-chart flows
Hanlin Yu
Søren Hauberg
Marcelo Hartmann
Arto Klami
Georgios Arvanitidis
AI4CE
286
2
0
30 May 2025
Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models
Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models
Louis Bethune
David Vigouroux
Yilun Du
Rufin VanRullen
Thomas Serre
Victor Boutin
DiffM
596
2
0
23 May 2025
Accurate Forgetting for Heterogeneous Federated Continual Learning
Accurate Forgetting for Heterogeneous Federated Continual LearningInternational Conference on Learning Representations (ICLR), 2025
Abudukelimu Wuerkaixi
Sen Cui
J.N. Zhang
Kunda Yan
Bo Han
Gang Niu
Lei Fang
Changshui Zhang
Masashi Sugiyama
576
23
0
20 Feb 2025
Diffusion Generative Modeling on Lie Group Representations
Diffusion Generative Modeling on Lie Group Representations
Marco Bertolini
Tuan Le
Djork-Arné Clevert
DiffM
530
2
0
04 Feb 2025
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based ModelsNeural Information Processing Systems (NeurIPS), 2024
Daniela de Albuquerque
John Pearson
DiffM
484
2
0
03 Jan 2025
Analyzing Generative Models by Manifold Entropic Metrics
Analyzing Generative Models by Manifold Entropic MetricsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Daniel Galperin
Ullrich Köthe
DRL
473
1
0
25 Oct 2024
Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax
Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax
I. Butakov
Alexander Sememenko
Alexander Tolmachev
Andrey Gladkov
Marina Munkhoeva
Alexey Frolov
461
3
0
09 Oct 2024
A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models
A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models
Shivam Kumar
Yun Yang
Lizhen Lin
312
2
0
02 Oct 2024
Improved Image Classification with Manifold Neural Networks
Improved Image Classification with Manifold Neural Networks
Caio F. Deberaldini Netto
Zhiyang Wang
Luana Ruiz
AI4CE
310
2
0
19 Sep 2024
Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups
Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups
Yuchen Zhu
Tianrong Chen
Lingkai Kong
Evangelos A. Theodorou
Molei Tao
DiffM
343
15
0
25 May 2024
FUSE: Fast Unified Simulation and Estimation for PDEs
FUSE: Fast Unified Simulation and Estimation for PDEsNeural Information Processing Systems (NeurIPS), 2024
Levi E. Lingsch
Dana Grund
Siddhartha Mishra
Georgios Kissas
AI4CE
373
5
0
23 May 2024
A Geometric Explanation of the Likelihood OOD Detection Paradox
A Geometric Explanation of the Likelihood OOD Detection Paradox
Hamidreza Kamkari
Brendan Leigh Ross
Jesse C. Cresswell
M. Volkovs
Rahul G. Krishnan
Gabriel Loaiza-Ganem
OODD
413
18
0
27 Mar 2024
Mutual Information Estimation via Normalizing Flows
Mutual Information Estimation via Normalizing Flows
I. Butakov
Alexander Tolmachev
S. Malanchuk
A. Neopryatnaya
Alexey Frolov
371
18
0
04 Mar 2024
Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees
Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees
Sean Jaffe
A. Davydov
Deniz Lapsekili
Ambuj K. Singh
Francesco Bullo
414
8
0
12 Feb 2024
Neural Contractive Dynamical Systems
Neural Contractive Dynamical SystemsInternational Conference on Learning Representations (ICLR), 2024
Hadi Beik-Mohammadi
Søren Hauberg
Georgios Arvanitidis
Nadia Figueroa
Gerhard Neumann
Leonel Rozo
333
14
0
17 Jan 2024
Unified framework for diffusion generative models in SO(3): applications
  in computer vision and astrophysics
Unified framework for diffusion generative models in SO(3): applications in computer vision and astrophysics
Yesukhei Jagvaral
F. Lanusse
Rachel Mandelbaum
DiffM
318
9
0
18 Dec 2023
Deep Generative Models for Detector Signature Simulation: A Taxonomic
  Review
Deep Generative Models for Detector Signature Simulation: A Taxonomic ReviewReviews in Physics (RP), 2023
Baran Hashemi
Claudius Krause
409
33
0
15 Dec 2023
Multivariate Scenario Generation of Day-Ahead Electricity Prices using
  Normalizing Flows
Multivariate Scenario Generation of Day-Ahead Electricity Prices using Normalizing FlowsApplied Energy (Appl. Energy), 2023
Hannes Hilger
D. Witthaut
Manuel Dahmen
L. R. Gorjão
Julius Trebbien
Eike Cramer
249
9
0
23 Nov 2023
Scaling Riemannian Diffusion Models
Scaling Riemannian Diffusion ModelsNeural Information Processing Systems (NeurIPS), 2023
Aaron Lou
Minkai Xu
Stefano Ermon
275
14
0
30 Oct 2023
Canonical normalizing flows for manifold learning
Canonical normalizing flows for manifold learningNeural Information Processing Systems (NeurIPS), 2023
Kyriakos Flouris
E. Konukoglu
DRL
590
16
0
19 Oct 2023
Simple Mechanisms for Representing, Indexing and Manipulating Concepts
Simple Mechanisms for Representing, Indexing and Manipulating Concepts
Yuanzhi Li
Raghu Meka
Rina Panigrahy
Kulin Shah
260
1
0
18 Oct 2023
Self-supervised Representation Learning From Random Data Projectors
Self-supervised Representation Learning From Random Data ProjectorsInternational Conference on Learning Representations (ICLR), 2023
Yi Sui
Tongzi Wu
Jesse C. Cresswell
Ga Wu
George Stein
Xiao Shi Huang
Xiaochen Zhang
Anthony L. Caterini
496
17
0
11 Oct 2023
Implicit Variational Inference for High-Dimensional Posteriors
Implicit Variational Inference for High-Dimensional PosteriorsNeural Information Processing Systems (NeurIPS), 2023
Anshuk Uppal
Kristoffer Stensbo-Smidt
Wouter Boomsma
J. Frellsen
BDL
385
4
0
10 Oct 2023
On Explicit Curvature Regularization in Deep Generative Models
On Explicit Curvature Regularization in Deep Generative Models
Yonghyeon Lee
Frank C. Park
BDL
273
15
0
19 Sep 2023
Learning Nonparametric High-Dimensional Generative Models: The
  Empirical-Beta-Copula Autoencoder
Learning Nonparametric High-Dimensional Generative Models: The Empirical-Beta-Copula Autoencoder
Maximilian Coblenz
Oliver Grothe
Fabian Kächele
SyDaDRL
281
0
0
18 Sep 2023
Computing excited states of molecules using normalizing flows
Computing excited states of molecules using normalizing flowsJournal of Chemical Theory and Computation (JCTC), 2023
Yahya Saleh
Álvaro Fernández Corral
Emil Vogt
Armin Iske
J. Küpper
A. Yachmenev
453
10
0
31 Aug 2023
Out-of-distribution detection using normalizing flows on the data manifold
Out-of-distribution detection using normalizing flows on the data manifold
S. Razavi
M. Mehmanchi
Reshad Hosseini
Mostafa Tavassolipour
OODD
469
1
0
26 Aug 2023
Calorimeter shower superresolution
Calorimeter shower superresolution
Ian Pang
C. Pollard
David Shih
DiffM
272
13
0
22 Aug 2023
A Review of Change of Variable Formulas for Generative Modeling
A Review of Change of Variable Formulas for Generative Modeling
Ullrich Kothe
305
14
0
04 Aug 2023
InVAErt networks: a data-driven framework for model synthesis and
  identifiability analysis
InVAErt networks: a data-driven framework for model synthesis and identifiability analysisComputer Methods in Applied Mechanics and Engineering (CMAME), 2023
Guoxiang Grayson Tong
Carlos A. Sing Long
Daniele E. Schiavazzi
395
11
0
24 Jul 2023
Sig-Splines: universal approximation and convex calibration of time
  series generative models
Sig-Splines: universal approximation and convex calibration of time series generative models
Magnus Wiese
Phillip Murray
R. Korn
AI4TS
315
2
0
19 Jul 2023
Vector Quantile Regression on Manifolds
Vector Quantile Regression on ManifoldsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Marco Pegoraro
S. Vedula
Aviv A. Rosenberg
Irene Tallini
Emanuele Rodolà
A. Bronstein
409
2
0
03 Jul 2023
Lifting Architectural Constraints of Injective Flows
Lifting Architectural Constraints of Injective FlowsInternational Conference on Learning Representations (ICLR), 2023
Peter Sorrenson
Felix Dräxler
Armand Rousselot
Sander Hummerich
Leandro Zimmerman
Ullrich Kothe
TPMAI4CE
481
14
0
02 Jun 2023
ELSA -- Enhanced latent spaces for improved collider simulations
ELSA -- Enhanced latent spaces for improved collider simulations
Benjamin Nachman
R. Winterhalder
318
16
0
12 May 2023
SINCERE: Sequential Interaction Networks representation learning on
  Co-Evolving RiEmannian manifolds
SINCERE: Sequential Interaction Networks representation learning on Co-Evolving RiEmannian manifoldsThe Web Conference (WWW), 2023
Junda Ye
Zhongbao Zhang
Li Sun
Yang Yan
Feiyang Wang
Fuxin Ren
166
9
0
06 May 2023
TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional
  Generation
TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional GenerationInternational Conference on Machine Learning (ICML), 2023
Zhaoyan Liu
Noël Vouitsis
S. Gorti
Jimmy Ba
Gabriel Loaiza-Ganem
ViT
387
2
0
26 Apr 2023
Explicitly Minimizing the Blur Error of Variational Autoencoders
Explicitly Minimizing the Blur Error of Variational AutoencodersInternational Conference on Learning Representations (ICLR), 2023
G. Bredell
Kyriakos Flouris
K. Chaitanya
Ertunc Erdil
E. Konukoglu
203
42
0
12 Apr 2023
Diffusion map particle systems for generative modeling
Diffusion map particle systems for generative modelingFoundations of Data Science (FDS), 2023
Fengyi Li
Youssef Marzouk
DiffM
342
6
0
01 Apr 2023
Conformal Generative Modeling on Triangulated Surfaces
Conformal Generative Modeling on Triangulated Surfaces
Victor D. Dorobantu
Charlotte Borcherds
Yisong Yue
222
1
0
17 Mar 2023
Injectivity of ReLU networks: perspectives from statistical physics
Injectivity of ReLU networks: perspectives from statistical physicsApplied and Computational Harmonic Analysis (ACHA), 2023
Antoine Maillard
Afonso S. Bandeira
David Belius
Ivan Dokmanić
S. Nakajima
186
11
0
27 Feb 2023
Master's Thesis: Out-of-distribution Detection with Energy-based Models
Master's Thesis: Out-of-distribution Detection with Energy-based Models
Sven Elflein
OODD
295
2
0
28 Jan 2023
Neural Wasserstein Gradient Flows for Maximum Mean Discrepancies with
  Riesz Kernels
Neural Wasserstein Gradient Flows for Maximum Mean Discrepancies with Riesz KernelsInternational Conference on Machine Learning (ICML), 2023
Fabian Altekrüger
J. Hertrich
Gabriele Steidl
415
15
0
27 Jan 2023
Deep Injective Prior for Inverse Scattering
Deep Injective Prior for Inverse ScatteringIEEE Transactions on Antennas and Propagation (IEEE Trans. Antennas Propag.), 2023
AmirEhsan Khorashadizadeh
Vahid Khorashadi-Zadeh
Sepehr Eskandari
Guy A. E. Vandenbosch
Ivan Dokmanić
284
12
0
08 Jan 2023
123
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