Integrity report for SPLIT-PINN: Separable Probability Learning Technique via Physics-Informed Neural Networks for High-Dimensional Probabilistic Modeling

A machine-verified record of the checks Pith has run against this paper: detector runs, findings, signed bundle events, and canonical identifiers.

arXiv:2606.04000 · pith:2026:B4BDRWWZBJCJ2Z5RMOETZVDHNE

Paper page arXiv integrity.json bundle.json

Detector runs

Findings

Signed record

The machine-readable record for this paper lives at /pith/B4BDRWWZBJCJ2Z5RMOETZVDHNE/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.