Normalizing Flows on Tori and Spheres

6 February 2020

Danilo Jimenez Rezende

Papers citing "Normalizing Flows on Tori and Spheres"

50 / 102 papers shown

Title
Ergodic Generative Flows Leo Maxime Brunswic Mateo Clemente Rui Heng Yang Adam Sigal Amir Rasouli Yinchuan Li 47 0 0 06 May 2025
Riemannian Neural Geodesic Interpolant Jiawen Wu Bingguang Chen Yuyi Zhou Qi Meng Rongchan Zhu Zhi-Ming Ma 29 0 0 22 Apr 2025
Spherical Tree-Sliced Wasserstein Distance Hoang V. Tran Thanh T. Chu K. Nguyen Trang Pham Tam Le Trung Quoc Nguyen OT 63 3 0 14 Mar 2025
NeuMC -- a package for neural sampling for lattice field theories Piotr Bialas P. Korcyl T. Stebel Dawid Zapolski 39 0 0 14 Mar 2025
Flows on convex polytopes Tomek Diederen Nicola Zamboni 50 0 0 13 Mar 2025
Riemann $^2$ : Learning Riemannian Submanifolds from Riemannian Data Leonel Rozo Miguel González-Duque Noémie Jaquier Søren Hauberg 65 1 0 07 Mar 2025
Provably Efficient Exploration in Reward Machines with Low Regret Hippolyte Bourel Anders Jonsson Odalric-Ambrym Maillard Chenxiao Ma M. S. Talebi 34 0 0 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 48 0 0 31 Oct 2024
Training Neural Samplers with Reverse Diffusive KL Divergence Jiajun He Wenlin Chen Mingtian Zhang David Barber José Miguel Hernández-Lobato DiffM 47 4 0 16 Oct 2024
Neural Product Importance Sampling via Warp Composition Joey Litalien Miloš Hašan Fujun Luan Krishna Mullia Iliyan Georgiev 31 0 0 12 Sep 2024
Efficient mapping of phase diagrams with conditional Boltzmann Generators Maximilian Schebek Michele Invernizzi Frank Noé Jutta Rogal 52 8 0 18 Jun 2024
Multi-level Interaction Modeling for Protein Mutational Effect Prediction Yuanle Mo Xin Hong Bowen Gao Yinjun Jia Yanyan Lan AI4CE 34 2 0 28 May 2024
Fast and Unified Path Gradient Estimators for Normalizing Flows Lorenz Vaitl Ludwig Winkler Lorenz Richter Pan Kessel 44 4 0 23 Mar 2024
Nonparametric Automatic Differentiation Variational Inference with Spline Approximation Yuda Shao Shan Yu Tianshu Feng 34 1 0 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 62 12 0 05 Mar 2024
Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations Henrik Schopmans Pascal Friederich AI4CE 33 1 0 02 Feb 2024
Equivariant Manifold Neural ODEs and Differential Invariants Emma Andersdotter Fredrik Ohlsson 39 0 0 25 Jan 2024
Manifold GCN: Diffusion-based Convolutional Neural Network for Manifold-valued Graphs M. Hanik Gabriele Steidl C. V. Tycowicz GNN MedIm 43 3 0 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 50 7 0 08 Jan 2024
Contrastive Sequential Interaction Network Learning on Co-Evolving Riemannian Spaces Li Sun Junda Ye Jiawei Zhang Yong Yang Mingsheng Liu Feiyang Wang Philip S. Yu 54 5 0 02 Jan 2024
Learning Distributions on Manifolds with Free-form Flows Peter Sorrenson Felix Dräxler Armand Rousselot Sander Hummerich Ullrich Kothe DRL AI4CE 34 2 0 15 Dec 2023
Unbiasing Enhanced Sampling on a High-dimensional Free Energy Surface with Deep Generative Model Yikai Liu Tushar K. Ghosh Guang Lin Ming Chen DiffM 40 1 0 14 Dec 2023
Topological Obstructions and How to Avoid Them Babak Esmaeili Robin Walters Heiko Zimmermann Jan-Willem van de Meent AI4CE 31 3 0 12 Dec 2023
Flow Symmetrization for Parameterized Constrained Diffeomorphisms Aalok Gangopadhyay Dwip Dalal Progyan Das Shanmuganathan Raman 48 0 0 11 Dec 2023
Transition Path Sampling with Boltzmann Generator-based MCMC Moves Michael Plainer Hannes Stärk Charlotte Bunne Stephan Günnemann 31 6 0 08 Dec 2023
Canonical normalizing flows for manifold learning Kyriakos Flouris E. Konukoglu DRL 67 7 0 19 Oct 2023
Riemannian Residual Neural Networks Isay Katsman Eric Chen Sidhanth Holalkere Anna Asch Aaron Lou Ser-Nam Lim Christopher De Sa 26 10 0 16 Oct 2023
Generative Modeling on Manifolds Through Mixture of Riemannian Diffusion Processes Jaehyeong Jo Sung Ju Hwang DiffM 42 9 0 11 Oct 2023
Conditional normalizing flows for IceCube event reconstruction Yu-Hsiang Lan BDL 14 2 0 28 Sep 2023
Training normalizing flows with computationally intensive target probability distributions P. Białas P. Korcyl T. Stebel 18 5 0 25 Aug 2023
SE(3) Equivariant Augmented Coupling Flows Laurence I. Midgley Vincent Stimper Javier Antorán Emile Mathieu Bernhard Schölkopf José Miguel Hernández-Lobato 47 23 0 20 Aug 2023
A Review of Change of Variable Formulas for Generative Modeling Ullrich Kothe 34 6 0 04 Aug 2023
Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints Alistair J R White Niki Kilbertus Maximilian Gelbrecht Niklas Boers 22 6 0 16 Jun 2023
Spontaneous Symmetry Breaking in Generative Diffusion Models G. Raya L. Ambrogioni DiffM 17 30 0 31 May 2023
Confronting Ambiguity in 6D Object Pose Estimation via Score-Based Diffusion on SE(3) Tsu-Ching Hsiao Haoming Chen Hsuan-Kung Yang Chun-Yi Lee DiffM 23 7 0 25 May 2023
SINCERE: Sequential Interaction Networks representation learning on Co-Evolving RiEmannian manifolds Junda Ye Zhongbao Zhang Li Sun Yang Yan Feiyang Wang Fuxin Ren 30 6 0 06 May 2023
Machine Learning and the Future of Bayesian Computation Steven Winter Trevor Campbell Lizhen Lin Sanvesh Srivastava David B. Dunson TPM 47 4 0 21 Apr 2023
Implicit representation priors meet Riemannian geometry for Bayesian robotic grasping Norman Marlier Julien Gustin O. Bruls Gilles Louppe 36 0 0 18 Apr 2023
Delving into Discrete Normalizing Flows on SO(3) Manifold for Probabilistic Rotation Modeling Yulin Liu Haoran Liu Yingda Yin Yang Wang Baoquan Chen Heru Wang 32 13 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 35 0 0 23 Feb 2023
Flow Matching on General Geometries Ricky T. Q. Chen Y. Lipman AI4CE 34 67 0 07 Feb 2023
Rigid Body Flows for Sampling Molecular Crystal Structures Jonas Köhler Michele Invernizzi P. D. Haan Frank Noé AI4CE 44 27 0 26 Jan 2023
normflows: A PyTorch Package for Normalizing Flows Vincent Stimper David Liu Andrew Campbell V. Berenz Lukas Ryll Bernhard Schölkopf José Miguel Hernández-Lobato AI4CE 24 56 0 26 Jan 2023
On the Robustness of Normalizing Flows for Inverse Problems in Imaging Seongmin Hong I. Park S. Chun 43 7 0 08 Dec 2022
Denoising Deep Generative Models G. Loaiza-Ganem Brendan Leigh Ross Luhuan Wu John P. Cunningham Jesse C. Cresswell Anthony L. Caterini DiffM 36 5 0 30 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
Learning Riemannian Stable Dynamical Systems via Diffeomorphisms Jiechao Zhang Hadi Beik-Mohammadi Leonel Rozo 28 15 0 06 Nov 2022
Atlas flow : compatible local structures on the manifold Taejin Paik Jaemin Park J. Park 39 0 0 24 Oct 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
Matching Normalizing Flows and Probability Paths on Manifolds Heli Ben-Hamu Samuel N. Cohen Joey Bose Brandon Amos Aditya Grover Maximilian Nickel Ricky T. Q. Chen Y. Lipman 63 39 0 11 Jul 2022