Chapter 1 Rho-Tau Embedding of Statistical Models

Chapter 2 A Class of Non-parametric Deformed Exponential Statistical Models

Chapter 3 Statistical Manifolds Admitting Torsion and Partially Flat Spaces

Chapter 4 Conformal Flattening on the Probability Simplex and Its Applications to Voronoi Partitions and Centroids

Chapter 5 Monte Carlo Information-Geometric Structures

Chapter 6 Information Geometry in Portfolio Theory

Chapter 8 Some Universal Insights on Divergences for Statistics, Machine Learning and Artificial Intelligence

Chapter 9 Information-Theoretic Matrix Inequalities and Diffusion Processes on Unimodular Lie Groups

Chapter 10 Warped Riemannian Metrics for Location-Scale Models

Chapter 11 Clustering in Hilbert’s Projective Geometry: The Case Studies of the Probability Simplex and the Elliptope of Correlation Matrices

Chapter 12 Jean-Louis Koszul and the Elementary Structures of Information Geometry