New Laplacian comparison theorem and its applications to diffusion processes on Riemannian manifolds

Canonical Correlation Analysis on Riemannian Manifolds and Its Applications

Canonical correlation analysis (CCA) is a widely used statistical technique to capture correlations between two sets of multi-variate random variables and has found a multitude of applications in computer vision, medical imaging and machine learning. The classical formulation assumes that the data live in a pair of vector spaces which makes its use in certain important scientific domains proble...

Diffusion Processes on Manifolds

This is an informal introduction to stochastic analysis on both Riemanian and Lorentzian manifolds. We review the basics underlying the construction of diffusions on manifolds, highlighting the important differences between the Riemanian and Lorentzian cases. We also discuss a few recent applications which range from biophysics to cosmology.

The Hodge theorem for Riemannian manifolds

on the comparison of keyword and semantic-context methods of learning new vocabulary meaning

the rationale behind the present study is that particular learning strategies produce more effective results when applied together. the present study tried to investigate the efficiency of the semantic-context strategy alone with a technique called, keyword method. to clarify the point, the current study seeked to find answer to the following question: are the keyword and semantic-context metho...

The Gauss-Bonnet-Chern Theorem on Riemannian Manifolds

This expository paper contains a detailed introduction to some important works concerning the Gauss-Bonnet-Chern theorem. The study of this theorem has a long history dating back to Gauss’s Theorema Egregium (Latin: Remarkable Theorem) and culminated in Chern’s groundbreaking work [14] in 1944, which is a deep and wonderful application of Elie Cartan’s formalism. The idea and tools in [14] have...