This content will become publicly available on December 1, 2026

Title: The Value of Out-of-distribution Data
Award ID(s):
2031985
PAR ID:
10657371
Author(s) / Creator(s):
; ; ; ;
Publisher / Repository:
NeurIPS
Date Published:
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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    A unified approach to the determination of eigenvalues and eigenvectors of specific matrices associated with directed graphs is presented. Matrices studied include the new distance matrix, with natural extensions to the distance Laplacian and distance signless Laplacian, in addition to the new adjacency matrix, with natural extensions to the Laplacian and signless Laplacian. Various sums of Kronecker products of nonnegative matrices are introduced to model the Cartesian and lexicographic products of digraphs. The Jordan canonical form is applied extensively to the analysis of spectra and eigenvectors. The analysis shows that Cartesian products provide a method for building infinite families of transmission regular digraphs with few distinct distance eigenvalues. 
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