From Bayesian inference to MCMC and convex optimisation in Hadamard manifolds

DOI10.1007/978-3-030-80209-7_1OpenAlexW3182737390MaRDI QIDQ2117815

Jonathan H. Manton, Salem Said, Nicolas Le Bihan

Publication date: 22 March 2022

Full work available at URL: https://doi.org/10.1007/978-3-030-80209-7_1

zbMATH Keywords

Gaussian distributionBayesian inferenceHadamard manifoldMCMCconvex optimisation

Mathematics Subject Classification ID

Bayesian inference (62F15) Convex programming (90C25)

Related Items (1)

Tracking and Regret Bounds for Online Zeroth-Order Euclidean and Riemannian Optimization

Cites Work

• Markov chains and stochastic stability
• General state space Markov chains and MCMC algorithms
• Large sample theory of intrinsic and extrinsic sample means on manifolds. I
• The Kähler Mean of Block-Toeplitz Matrices with Toeplitz Structured Blocks
• Gaussian Distributions on Riemannian Symmetric Spaces: Statistical Learning With Structured Covariance Matrices
• Visualizing hyperbolic Voronoi diagrams
• Riemannian Gaussian Distributions on the Space of Symmetric Positive Definite Matrices
• Riemannian Geometry

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