Affine-Invariant Orders on the Set of Positive-Definite Matrices. - Cyrus Mostajeran; Rodolphe Sepulchre (GSI, 2017)

Monotonicity on homogeneous spaces. - Cyrus Mostajeran; Rodolphe Sepulchre (Math. Control. Signals Syst., 2018)

Positivity, Monotonicity, and Consensus on Lie Groups. - Cyrus Mostajeran; Rodolphe Sepulchre (SIAM J. Control. Optim., 2018)

Affine-Invariant Midrange Statistics. - Cyrus Mostajeran; Christian Grussler; Rodolphe Sepulchre (GSI, 2019)

Inductive Geometric Matrix Midranges. - Graham W. Van Goffrier; Cyrus Mostajeran; Rodolphe Sepulchre (CoRR, 2020)

Geometric Matrix Midranges. - Cyrus Mostajeran; Christian Grussler; Rodolphe Sepulchre (SIAM J. Matrix Anal. Appl., 2020)

Target formation on the circle by monotone system design. - Cyrus Mostajeran; Jin Gyu Lee; Graham W. Van Goffrier; Rodolphe Sepulchre (CDC, 2021)

Gaussian Distributions on Riemannian Symmetric Spaces in the Large N Limit. - Simon Heuveline; Salem Said; Cyrus Mostajeran (GSI, 2021)

Online Learning of Riemannian Hidden Markov Models in Homogeneous Hadamard Spaces. - Quinten Tupker; Salem Said; Cyrus Mostajeran (GSI, 2021)

Node-wise monotone barrier coupling law for central pattern generation. - Jin Gyu Lee; Cyrus Mostajeran; Graham W. Van Goffrier (CoRR, 2022)

Geometric Learning of Hidden Markov Models via a Method of Moments Algorithm. - Berlin Chen; Cyrus Mostajeran; Salem Said (CoRR, 2022)

The Gaussian Kernel on the Circle and Spaces that Admit Isometric Embeddings of the Circle. - Nathaël Da Costa; Cyrus Mostajeran; Juan-Pablo Ortega (GSI (1), 2023)

Determinantal Expressions of Certain Integrals on Symmetric Spaces. - Salem Said; Cyrus Mostajeran (GSI (1), 2023)

Geometric Learning with Positively Decomposable Kernels. - Nathaël Da Costa; Cyrus Mostajeran; Juan-Pablo Ortega; Salem Said (CoRR, 2023)

Invariant kernels on Riemannian symmetric spaces: a harmonic-analytic approach. - Nathaël Da Costa; Cyrus Mostajeran; Juan-Pablo Ortega; Salem Said (CoRR, 2023)

Riemannian Statistics Meets Random Matrix Theory: Toward Learning From High-Dimensional Covariance Matrices. - Salem Said; Simon Heuveline; Cyrus Mostajeran (IEEE Trans. Inf. Theory, 2023)

Geometric statistics with subspace structure preservation for SPD matrices. - Cyrus Mostajeran; Nathaël Da Costa; Graham W. Van Goffrier; Rodolphe Sepulchre (CoRR, 2024)

Differential Geometry with Extreme Eigenvalues in the Positive Semidefinite Cone. - Cyrus Mostajeran; Nathaël Da Costa; Graham W. Van Goffrier; Rodolphe Sepulchre (SIAM J. Matrix Anal. Appl., 2024)

Node-Wise Monotone Barrier Coupling Law for Formation Control. - Jin Gyu Lee; Cyrus Mostajeran; Graham W. Van Goffrier (Entropy, 2024)

Universal kernels via harmonic analysis on Riemannian symmetric spaces. - Franziskus Steinert; Salem Said; Cyrus Mostajeran (CoRR, 2025)