Metraipolis › archive › dc_462ebac832ef

TI$^2$PS: A Topology-Informed Inverse Design Framework for Stochastic Multicellular Pattern Formation — arXiv:2608.27931

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.27931
License (as archived): CC0-1.0
Archived: 2026-10-17T11:06:28.979Z
SHA-256 of the archived text: 6a55c813327129a21ad9304a8ca67db05ef6070c09d35ab8c58ad662bea5b2f2
Stable URL of this page: https://metraipolis.com/documento/dc_462ebac832ef

How to cite

TI$^2$PS: A Topology-Informed Inverse Design Framework for Stochastic Multicellular Pattern Formation — arXiv:2608.27931 — arXiv (en), https://arxiv.org/abs/2608.27931 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_462ebac832ef (Metraipolis archive dc_462ebac832ef, sha256 6a55c813327129a21ad9304a8ca67db05ef6070c09d35ab8c58ad662bea5b2f2)

BibTeX

@misc{dc462ebac832ef,
  title = {TI$^2$PS: A Topology-Informed Inverse Design Framework for Stochastic Multicellular Pattern Formation — arXiv:2608.27931},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.27931},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_462ebac832ef; sha256 6a55c813327129a21ad9304a8ca67db05ef6070c09d35ab8c58ad662bea5b2f2},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.27931. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

This study proposes a novel framework to estimate parameters for reproducing target multicellular patterns using an agent-based model (ABM). Two major challenges in multicellular ABMs are estimating cell-level parameters (agent-specific variables) and quantitatively evaluating the topological characteristics of multicellular arrangements under stochastic cell proliferation and death. To address these challenges, we integrate two approaches: Betti vectors and inverse surrogate modeling. The Betti vectors obtained through topological data analysis can consistently represent features of a wide range of multicellular spatial configurations. The inverse surrogate modeling enables direct inference of the corresponding ABM parameters from the target patterns. We validated the proposed framework using zebrafish pigment pattern formation, a representative model of pattern formation driven by multicellular interactions. The results demonstrate that our framework successfully estimates ABM parameters and outperforms conventional methods such as PointNet++. Notably, the proposed method, which used only 10% of the training data, outperformed PointNet++, which used 100% of the data, across all evaluation metrics.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-08-31 in cs.LG).
Categorie arXiv: Machine Learning (cs.LG).
Pagina del lavoro: https://arxiv.org/abs/2608.27931 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-17T10:50:25.785Z dalla pagina https://arxiv.org/catchup/cs.LG/2026-08-31?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).