exhilaration
发表于 2025-3-25 05:09:39
It is quite confusing isn’t it?ifferent deformations. For the related Large Deformation Diffemorphic Metric Mapping, which yields unstructured deformations, this issue was addressed in [.] introducing object boundary constraints. We develop a new registration problem, marrying the two frameworks to allow for different constrained deformations in different coupled shapes.
去掉
发表于 2025-3-25 09:10:05
https://doi.org/10.1007/978-1-349-24135-4s known and sample diffusion means can therefore be calculated. As an example, we investigate a classic data set from directional statistics, for which the sample Fréchet mean exhibits finite sample smeariness.
天赋
发表于 2025-3-25 14:07:32
http://reply.papertrans.cn/39/3837/383604/383604_23.png
CROAK
发表于 2025-3-25 18:03:30
Diffusion Means and Heat Kernel on Manifoldss known and sample diffusion means can therefore be calculated. As an example, we investigate a classic data set from directional statistics, for which the sample Fréchet mean exhibits finite sample smeariness.
CESS
发表于 2025-3-25 22:41:58
From Bayesian Inference to MCMC and Convex Optimisation in Hadamard Manifoldss which are also symmetric spaces). To investigate this problem, it introduces new tools for Markov Chain Monte Carlo, and convex optimisation: (1) it provides easy-to-verify sufficient conditions for the geometric ergodicity of an isotropic Metropolis-Hastings Markov chain, in a symmetric Hadamard
审问,审讯
发表于 2025-3-26 02:56:16
Finite Sample Smeariness on Spheresave as if it were smeary for quite large regimes of finite sample sizes. In effect classical quantile-based statistical testing procedures do not preserve nominal size, they reject too often under the null hypothesis. Suitably designed bootstrap tests, however, amend for FSS. On the circle it has be
GLOSS
发表于 2025-3-26 08:02:37
http://reply.papertrans.cn/39/3837/383604/383604_27.png
小隔间
发表于 2025-3-26 11:43:13
http://reply.papertrans.cn/39/3837/383604/383604_28.png
cringe
发表于 2025-3-26 15:42:29
Online Learning of Riemannian Hidden Markov Models in Homogeneous Hadamard Spaceshere observations lie in Riemannian manifolds based on the Baum-Welch algorithm suffered from high memory usage and slow speed. Here we present an algorithm that is online, more accurate, and offers dramatic improvements in speed and efficiency.
矛盾
发表于 2025-3-26 19:06:26
http://reply.papertrans.cn/39/3837/383604/383604_30.png