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2002.02428
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Normalizing Flows on Tori and Spheres
International Conference on Machine Learning (ICML), 2020
6 February 2020
Danilo Jimenez Rezende
George Papamakarios
S. Racanière
M. S. Albergo
G. Kanwar
P. Shanahan
Kyle Cranmer
TPM
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Papers citing
"Normalizing Flows on Tori and Spheres"
50 / 111 papers shown
Covering-Space Normalizing Flows: Approximating Pushforwards on Lens Spaces
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Anastasios L. Kesidis
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Group-Equivariant Diffusion Models for Lattice Field Theory
Octavio Vega
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M. Marinković
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320
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30 Oct 2025
Generalised Flow Maps for Few-Step Generative Modelling on Riemannian Manifolds
Oscar Davis
M. S. Albergo
Nicholas M. Boffi
Michael Bronstein
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383
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24 Oct 2025
Amortized Active Generation of Pareto Sets
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Asiri Wijesinghe
Rafael Oliveira
Piotr Koniusz
Cheng Soon Ong
Edwin V. Bonilla
236
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23 Oct 2025
Learning Boltzmann Generators via Constrained Mass Transport
Christopher von Klitzing
Denis Blessing
Henrik Schopmans
Pascal Friederich
Gerhard Neumann
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400
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21 Oct 2025
Fisher-Bingham-like normalizing flows on the sphere
Thorsten Glüsenkamp
137
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06 Oct 2025
Recent Advances in Simulation-based Inference for Gravitational Wave Data Analysis
Bo-Hua Liang
He Wang
341
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Do LLMs Overthink Basic Math Reasoning? Benchmarking the Accuracy-Efficiency Tradeoff in Language Models
Gaurav Srivastava
Aafiya Hussain
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244
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Dongzhe Fan
Jiacheng Shen
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306
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12 Jun 2025
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Adam Sigal
Amir Rasouli
Yinchuan Li
317
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Riemannian Neural Geodesic Interpolant
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225
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NeuMC -- a package for neural sampling for lattice field theories
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324
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14 Mar 2025
Spherical Tree-Sliced Wasserstein Distance
International Conference on Learning Representations (ICLR), 2025
Hoang V. Tran
Thanh T. Chu
K. Nguyen
Trang Pham
Tam Le
Trung Quoc Nguyen
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359
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14 Mar 2025
Flows on convex polytopes
Tomek Diederen
Nicola Zamboni
317
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13 Mar 2025
Riemann
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Leonel Rozo
Miguel González-Duque
Noémie Jaquier
Søren Hauberg
344
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07 Mar 2025
Provably Efficient Exploration in Reward Machines with Low Regret
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Anders Jonsson
Odalric-Ambrym Maillard
Chenxiao Ma
M. S. Talebi
172
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26 Dec 2024
Projected Neural Differential Equations for Learning Constrained Dynamics
Alistair J R White
Anna Buttner
Maximilian Gelbrecht
Valentin Duruisseaux
Niki Kilbertus
Frank Hellmann
Niklas Boers
373
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31 Oct 2024
Training Neural Samplers with Reverse Diffusive KL Divergence
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Wenlin Chen
Jiajun He
Mingtian Zhang
David Barber
José Miguel Hernández-Lobato
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419
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Neural Product Importance Sampling via Warp Composition
ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia (SIGGRAPH Asia), 2024
Joey Litalien
Jian Yang
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Iliyan Georgiev
306
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Efficient mapping of phase diagrams with conditional Boltzmann Generators
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329
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Multi-level Interaction Modeling for Protein Mutational Effect Prediction
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Xin Hong
Bowen Gao
Yinjun Jia
Yanyan Lan
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311
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Fast and Unified Path Gradient Estimators for Normalizing Flows
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Lorenz Vaitl
Ludwig Winkler
Lorenz Richter
Pan Kessel
304
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23 Mar 2024
Nonparametric Automatic Differentiation Variational Inference with Spline Approximation
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Yuda Shao
Shan Yu
Tianshu Feng
264
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10 Mar 2024
PPFlow: Target-aware Peptide Design with Torsional Flow Matching
Haitao Lin
Odin Zhang
Huifeng Zhao
Dejun Jiang
Lirong Wu
Zicheng Liu
Yufei Huang
Stan Z. Li
412
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05 Mar 2024
Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations
Henrik Schopmans
Pascal Friederich
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436
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Equivariant Manifold Neural ODEs and Differential Invariants
Emma Andersdotter
Fredrik Ohlsson
292
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25 Jan 2024
Manifold GCN: Diffusion-based Convolutional Neural Network for Manifold-valued Graphs
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Gabriele Steidl
C. V. Tycowicz
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MedIm
538
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25 Jan 2024
Scalable Normalizing Flows Enable Boltzmann Generators for Macromolecules
Joseph C. Kim
David Bloore
Karan Kapoor
Jun Feng
Ming-Hong Hao
Mengdi Wang
292
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08 Jan 2024
Contrastive Sequential Interaction Network Learning on Co-Evolving Riemannian Spaces
International Journal of Machine Learning and Cybernetics (IJMLC), 2023
Li Sun
Junda Ye
Jiawei Zhang
Yong Yang
Mingsheng Liu
Feiyang Wang
Philip S. Yu
276
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02 Jan 2024
Learning Distributions on Manifolds with Free-form Flows
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Peter Sorrenson
Felix Dräxler
Armand Rousselot
Sander Hummerich
Ullrich Kothe
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367
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Yikai Liu
Tushar K. Ghosh
Guang Lin
Ming Chen
DiffM
320
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14 Dec 2023
Topological Obstructions and How to Avoid Them
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Babak Esmaeili
Robin Walters
Heiko Zimmermann
Jan-Willem van de Meent
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265
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Flow Symmetrization for Parameterized Constrained Diffeomorphisms
Aalok Gangopadhyay
Dwip Dalal
Progyan Das
Shanmuganathan Raman
327
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Transition Path Sampling with Boltzmann Generator-based MCMC Moves
Michael Plainer
Hannes Stärk
Charlotte Bunne
Stephan Günnemann
247
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08 Dec 2023
Canonical normalizing flows for manifold learning
Neural Information Processing Systems (NeurIPS), 2023
Kyriakos Flouris
E. Konukoglu
DRL
596
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19 Oct 2023
Riemannian Residual Neural Networks
Isay Katsman
Eric Chen
Sidhanth Holalkere
Anna Asch
Aaron Lou
Ser-Nam Lim
Christopher De Sa
290
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16 Oct 2023
Generative Modeling on Manifolds Through Mixture of Riemannian Diffusion Processes
International Conference on Machine Learning (ICML), 2023
Jaehyeong Jo
Sung Ju Hwang
DiffM
385
19
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11 Oct 2023
Conditional normalizing flows for IceCube event reconstruction
International Conference on Rebooting Computing (ICRC), 2023
Yu-Hsiang Lan
BDL
98
4
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28 Sep 2023
Training normalizing flows with computationally intensive target probability distributions
Computer Physics Communications (CPC), 2023
P. Białas
P. Korcyl
T. Stebel
298
6
0
25 Aug 2023
SE(3) Equivariant Augmented Coupling Flows
Neural Information Processing Systems (NeurIPS), 2023
Laurence I. Midgley
Vincent Stimper
Javier Antorán
Emile Mathieu
Bernhard Schölkopf
José Miguel Hernández-Lobato
564
41
0
20 Aug 2023
A Review of Change of Variable Formulas for Generative Modeling
Ullrich Kothe
306
14
0
04 Aug 2023
Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints
Neural Information Processing Systems (NeurIPS), 2023
Alistair J R White
Niki Kilbertus
Maximilian Gelbrecht
Niklas Boers
425
16
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16 Jun 2023
Spontaneous Symmetry Breaking in Generative Diffusion Models
Neural Information Processing Systems (NeurIPS), 2023
G. Raya
Luca Ambrogioni
DiffM
347
62
0
31 May 2023
Confronting Ambiguity in 6D Object Pose Estimation via Score-Based Diffusion on SE(3)
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Tsu-Ching Hsiao
Haoming Chen
Hsuan-Kung Yang
Chun-Yi Lee
DiffM
295
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25 May 2023
SINCERE: Sequential Interaction Networks representation learning on Co-Evolving RiEmannian manifolds
The Web Conference (WWW), 2023
Junda Ye
Zhongbao Zhang
Li Sun
Yang Yan
Feiyang Wang
Fuxin Ren
170
9
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Machine Learning and the Future of Bayesian Computation
Steven Winter
Trevor Campbell
Lizhen Lin
Sanvesh Srivastava
David B. Dunson
TPM
406
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Implicit representation priors meet Riemannian geometry for Bayesian robotic grasping
Norman Marlier
Julien Gustin
O. Bruls
Gilles Louppe
184
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18 Apr 2023
Delving into Discrete Normalizing Flows on SO(3) Manifold for Probabilistic Rotation Modeling
Computer Vision and Pattern Recognition (CVPR), 2023
Yulin Liu
Haoran Liu
Yingda Yin
Yang Wang
Baoquan Chen
Heru Wang
238
19
0
08 Apr 2023
Accurate Free Energy Estimations of Molecular Systems Via Flow-based Targeted Free Energy Perturbation
Soo-Jung Lee
Amr H. Mahmoud
M. Lill
212
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23 Feb 2023
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