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Geodesic Monte Carlo on Embedded Manifolds

25 January 2013

Papers citing "Geodesic Monte Carlo on Embedded Manifolds"

50 / 64 papers shown

Title
Geodesic Slice Sampler for Multimodal Distributions with Strong Curvature Bernardo Williams Hanlin Yu Hoang Phuc Hau Luu Georgios Arvanitidis Arto Klami 108 0 0 28 Feb 2025
Functional Gradient Flows for Constrained Sampling Shiyue Zhang Longlin Yu Ziheng Cheng Cheng Zhang 61 0 0 30 Oct 2024
Low-rank Bayesian matrix completion via geodesic Hamiltonian Monte Carlo on Stiefel manifolds Tiangang Cui Alex Gorodetsky 35 0 0 27 Oct 2024
Parameterizations for Gradient-based Markov Chain Monte Carlo on the Stiefel Manifold: A Comparative Study Masahiro Tanaka 79 1 0 12 Feb 2024
Riemannian Langevin Monte Carlo schemes for sampling PSD matrices with fixed rank Tianmin Yu Shixin Zheng Jianfeng Lu Govind Menon Xiangxiong Zhang 10 0 0 08 Sep 2023
Monte Carlo on manifolds in high dimensions Kerun Xu Miranda C. Holmes-Cerfon 53 2 0 21 Aug 2023
Warped geometric information on the optimisation of Euclidean functions M. Hartmann Bernardo Williams Hanlin Yu Mark Girolami Alessandro Barp Arto Klami 81 3 0 16 Aug 2023
On the convergence of dynamic implementations of Hamiltonian Monte Carlo and No U-Turn Samplers Alain Durmus Samuel Gruffaz Miika Kailas E. Saksman M. Vihola 71 5 0 07 Jul 2023
Learning Rate Free Sampling in Constrained Domains Louis Sharrock Lester W. Mackey Christopher Nemeth 78 2 0 24 May 2023
Implicit representation priors meet Riemannian geometry for Bayesian robotic grasping Norman Marlier Julien Gustin O. Bruls Gilles Louppe 76 0 0 18 Apr 2023
Geodesic slice sampling on the sphere Michael Habeck Mareike Hasenpflug Shantanu Kodgirwar Daniel Rudolf 82 10 0 19 Jan 2023
Sampling with Mollified Interaction Energy Descent Lingxiao Li Qiang Liu Anna Korba Mikhail Yurochkin Justin Solomon 70 17 0 24 Oct 2022
Unbiased constrained sampling with Self-Concordant Barrier Hamiltonian Monte Carlo Maxence Noble Valentin De Bortoli Alain Durmus 59 6 0 21 Oct 2022
Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent Ruqi Zhang Qiang Liu Xin T. Tong BDL DRL 52 12 0 12 Oct 2022
Generalized Fiducial Inference on Differentiable Manifolds Alexander C. Murph Jan Hannig Jonathan P. Williams 59 3 0 30 Sep 2022
Sampling Constrained Continuous Probability Distributions: A Review Shiwei Lan Lulu Kang 48 6 0 26 Sep 2022
Neural Implicit Manifold Learning for Topology-Aware Density Estimation Brendan Leigh Ross Gabriel Loaiza-Ganem Anthony L. Caterini Jesse C. Cresswell AI4CE 73 3 0 22 Jun 2022
Spherical Sliced-Wasserstein Clément Bonet P. Berg Nicolas Courty Françcois Septier Lucas Drumetz Minh Pham 95 27 0 17 Jun 2022
Randomized Time Riemannian Manifold Hamiltonian Monte Carlo Peter Whalley Daniel Paulin Benedict Leimkuhler 61 4 0 09 Jun 2022
Randomized geometric tools for anomaly detection in stock markets Cyril Bachelard Apostolos Chalkis Vissarion Fisikopoulos Elias P. Tsigaridas 55 1 0 08 May 2022
Efficient Random Walks on Riemannian Manifolds S. Schwarz M. Herrmann A. Sturm M. Wardetzky 52 7 0 02 Feb 2022
Dimension-independent Markov chain Monte Carlo on the sphere H. Lie Daniel Rudolf Björn Sprungk T. Sullivan 80 6 0 22 Dec 2021
An Efficient Scheme for Sampling in Constrained Domains S. Chaudhry Daniel Lautzenheiser K. Ghosh 31 3 0 21 Oct 2021
A Unifying and Canonical Description of Measure-Preserving Diffusions Alessandro Barp So Takao M. Betancourt Alexis Arnaudon Mark Girolami 77 17 0 06 May 2021
Evaluating the Implicit Midpoint Integrator for Riemannian Manifold Hamiltonian Monte Carlo James A. Brofos Roy R. Lederman 45 3 0 14 Feb 2021
Riemannian Langevin Algorithm for Solving Semidefinite Programs Mufan Li Murat A. Erdogdu 118 29 0 21 Oct 2020
Magnetic Manifold Hamiltonian Monte Carlo James A. Brofos Roy R. Lederman 20 5 0 15 Oct 2020
Fast Convergence of Langevin Dynamics on Manifold: Geodesics meet Log-Sobolev Tianlin Li Qi Lei Ioannis Panageas 65 20 0 11 Oct 2020
A Fully Bayesian Gradient-Free Supervised Dimension Reduction Method using Gaussian Processes Raphael Gautier Piyush Pandita Sayan Ghosh D. Mavris 29 3 0 08 Aug 2020
Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes Panagiotis Tsilifis Piyush Pandita Sayan Ghosh Valeria Andreoli T. Vandeputte Liping Wang 35 19 0 05 Aug 2020
Normal-bundle Bootstrap Ruda Zhang R. Ghanem 30 5 0 27 Jul 2020
A Wasserstein Minimum Velocity Approach to Learning Unnormalized Models Ziyu Wang Shuyu Cheng Yueru Li Jun Zhu Bo Zhang 69 14 0 18 Feb 2020
Simulating sticky particles: A Monte Carlo method to sample a stratification Miranda C. Holmes-Cerfon 48 10 0 21 Dec 2019
Multi-Rank Sparse and Functional PCA: Manifold Optimization and Iterative Deflation Techniques Michael Weylandt 48 4 0 28 Jul 2019
Monte Carlo simulation on the Stiefel manifold via polar expansion Michael Jauch P. Hoff David B. Dunson 49 31 0 18 Jun 2019
Rotation Invariant Householder Parameterization for Bayesian PCA Rajbir-Singh Nirwan Nils Bertschinger 37 6 0 12 May 2019
Probabilistic Permutation Synchronization using the Riemannian Structure of the Birkhoff Polytope Tolga Birdal Umut Simsekli 86 38 0 11 Apr 2019
Adversarial Networks for Camera Pose Regression and Refinement Mai Bui Christoph Baur Nassir Navab Slobodan Ilic Shadi Albarqouni GAN 130 20 0 15 Mar 2019
Hamiltonian Monte Carlo on Symmetric and Homogeneous Spaces via Symplectic Reduction Alessandro Barp A. Kennedy Mark Girolami 35 9 0 07 Mar 2019
Understanding MCMC Dynamics as Flows on the Wasserstein Space Chang-Shu Liu Jingwei Zhuo Jun Zhu 106 22 0 01 Feb 2019
Hamiltonian Monte-Carlo for Orthogonal Matrices V. Yanush D. Kropotov 30 1 0 23 Jan 2019
A Riemann-Stein Kernel Method Alessandro Barp Christine J. Oates Emilio Porcu Mark Girolami 90 22 0 11 Oct 2018
Random orthogonal matrices and the Cayley transform Michael Jauch P. Hoff David B. Dunson 129 19 0 05 Oct 2018
Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC Tolga Birdal Umut Simsekli M. Eken Slobodan Ilic 92 38 0 31 May 2018
Note on the geodesic Monte Carlo Andrew J Holbrook 30 2 0 14 May 2018
Stochastic Gradient Hamiltonian Monte Carlo with Variance Reduction for Bayesian Inference Zhize Li Tianyi Zhang Shuyu Cheng Jun Yu Li Jian Li BDL 69 18 0 29 Mar 2018
Riemannian Stein Variational Gradient Descent for Bayesian Inference Chang-rui Liu Jun Zhu 65 67 0 30 Nov 2017
Diversity-Promoting Bayesian Learning of Latent Variable Models P. Xie Jun Zhu Eric Xing 70 33 0 23 Nov 2017
Bayesian Inference over the Stiefel Manifold via the Givens Representation A. Pourzanjani Richard M. Jiang Brian Mitchell P. Atzberger Linda R. Petzold 70 6 0 25 Oct 2017
Geometry and Dynamics for Markov Chain Monte Carlo Alessandro Barp François‐Xavier Briol A. Kennedy Mark Girolami AI4CE 82 31 0 08 May 2017