Learning Gaussian Mixtures Using the Wasserstein-Fisher-Rao Gradient Flow

4 January 2023

Papers citing "Learning Gaussian Mixtures Using the Wasserstein-Fisher-Rao Gradient Flow"

22 / 22 papers shown

Title
Sequential Monte Carlo approximations of Wasserstein--Fisher--Rao gradient flows Francesca R. Crucinio Sahani Pathiraja 58 0 0 06 Jun 2025
Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach Haoxuan Chen Yinuo Ren Martin Renqiang Min Lexing Ying Zachary Izzo DiffM MedIm 77 2 0 04 Jun 2025
HAM: A Hyperbolic Step to Regulate Implicit Bias Tom Jacobs Advait Gadhikar Celia Rubio-Madrigal R. Burkholz 79 0 0 03 Jun 2025
Hellinger-Kantorovich Gradient Flows: Global Exponential Decay of Entropy Functionals Alexander Mielke Jia Jie Zhu 172 2 0 28 Jan 2025
Computational and Statistical Asymptotic Analysis of the JKO Scheme for Iterative Algorithms to update distributions Shang Wu Yazhen Wang 104 0 0 11 Jan 2025
Inclusive KL Minimization: A Wasserstein-Fisher-Rao Gradient Flow Perspective Jia-Jie Zhu 159 1 0 31 Oct 2024
Model-free Estimation of Latent Structure via Multiscale Nonparametric Maximum Likelihood Bryon Aragam Ruiyi Yang 145 0 0 29 Oct 2024
Fisher-Rao Gradient Flow: Geodesic Convexity and Functional Inequalities José A. Carrillo Yifan Chen Daniel Zhengyu Huang Jiaoyang Huang Dongyi Wei AI4CE 91 4 0 22 Jul 2024
Efficient, Multimodal, and Derivative-Free Bayesian Inference With Fisher-Rao Gradient Flows Yifan Chen Daniel Zhengyu Huang Jiaoyang Huang Sebastian Reich Andrew M. Stuart 74 7 0 25 Jun 2024
Interaction-Force Transport Gradient Flows E. Gladin Pavel Dvurechensky Alexander Mielke Jia Jie Zhu OT 95 6 0 27 May 2024
Geometry-Aware Instrumental Variable Regression Heiner Kremer Bernhard Schölkopf 85 0 0 19 May 2024
Channelling Multimodality Through a Unimodalizing Transport: Warp-U Sampler and Stochastic Bridge Sampling Fei Ding David E. Jones Shiyuan He Xiao-Li Meng OT 51 0 0 01 Jan 2024
Big Learning Expectation Maximization Yulai Cong Sijia Li 68 2 0 19 Dec 2023
Multi-Objective Optimization via Wasserstein-Fisher-Rao Gradient Flow Yinuo Ren Tesi Xiao Tanmay Gangwani A. Rangi Holakou Rahmanian Lexing Ying Subhajit Sanyal 65 4 0 22 Nov 2023
Hilbert's projective metric for functions of bounded growth and exponential convergence of Sinkhorn's algorithm Stephan Eckstein 129 8 0 07 Nov 2023
Minimizing Convex Functionals over Space of Probability Measures via KL Divergence Gradient Flow Rentian Yao Linjun Huang Yun Yang 84 4 0 01 Nov 2023
Estimating the Rate-Distortion Function by Wasserstein Gradient Descent Yibo Yang Stephan Eckstein Marcel Nutz Stephan Mandt 71 10 0 29 Oct 2023
Cramer Type Distances for Learning Gaussian Mixture Models by Gradient Descent Ruichong Zhang 58 0 0 13 Jul 2023
Non-Log-Concave and Nonsmooth Sampling via Langevin Monte Carlo Algorithms Tim Tsz-Kit Lau Han Liu Thomas Pock 97 4 0 25 May 2023
Wasserstein Gradient Flows for Optimizing Gaussian Mixture Policies Hanna Ziesche Leonel Rozo 72 5 0 17 May 2023
An Explicit Expansion of the Kullback-Leibler Divergence along its Fisher-Rao Gradient Flow Carles Domingo-Enrich Aram-Alexandre Pooladian MDE 92 12 0 23 Feb 2023
Local Minima Structures in Gaussian Mixture Models Yudong Chen Dogyoon Song Xumei Xi Yuqian Zhang 38 3 0 28 Sep 2020