CITATION.cff

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
type: software
title: "GROUPOID: Groupoid-based aggregation for federated learning on Riemannian manifolds"
version: 0.1.0.dev4
date-released: 2026-07-06
license: Apache-2.0
repository-code: "https://github.com/smaniches/GROUPOID"
doi: 10.5281/zenodo.20563974
identifiers:
  - type: doi
    value: 10.5281/zenodo.20563974
    description: "Concept DOI (all versions) — always resolves to the latest, mathematically corrected version. Cite this."
  - type: doi
    value: 10.5281/zenodo.20563975
    description: "Version DOI (v0.1.0.dev0) — SUPERSEDED. This snapshot predates the sheaf-Laplacian PSD, persistence-dimension, and cohomology corrections; do not cite for results. Use v0.1.0.dev1 or later."
authors:
  - family-names: Maniches
    given-names: Santiago
    email: santiago.maniches@gmail.com
    affiliation: TOPOLOGICA LLC
    orcid: "https://orcid.org/0009-0005-6480-1987"
keywords:
  - federated learning
  - Riemannian geometry
  - groupoid
  - sheaf theory
  - cohomology
  - topological data analysis
abstract: >-
  Research prototype exploring groupoid-based aggregation for federated
  learning on Riemannian manifolds. Implements transport groupoid
  morphisms, first cohomology (H^1) for consistency detection,
  cellular sheaf Laplacian for spectral analysis, and Karcher mean
  aggregation via geomstats.