Analysis of the physical Laplacian and the heat flow on a locally finite graph

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

Andreas Weber This is my paper · ORCID

classification math.SPmath.CO

keywords finiteflowgraphheatlaplacianlocallyphysicalanalysis

verification ladder T0 review T1 audit T2 compute T3 formal

No signed human review yet.

0 comments

read the original abstract

We study the physical Laplacian and the corresponding heat flow on an infinite, locally finite graph with possibly unbounded valence.

Forward citations

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

Spectro-Riemannian Graph Neural Networks
cs.LG 2025-02 conditional novelty 6.0 of 10

CUSP is a graph neural network that combines Ollivier-Ricci curvature with spectral filters on a product of hyperbolic, spherical, and Euclidean spaces, claiming SOTA results on eight node and link prediction benchmarks.