---
title: "Asier Gutiérrez-Fandiño"
type: "entity"
entity_kind: "person"
status: "hub"
canonical_name: "Asier Gutiérrez-Fandiño"
aliases: []
first_seen: "2026-07-12T00:00:00.000Z"
writer_model: "claude-sonnet-5"
connects_to: ["persistent homology","validation-set-free generalization estimation","persistence-diagram distance","topological data analysis","Tolga Birdal"]
---


First author of "Persistent Homology Captures the Generalization of Neural
Networks Without A Validation Set" (arXiv:2106.00012, 2021, with David
Pérez-Fernández, Jordi Armengol-Estapé & Marta Villegas) — the second of the
vault's two founding neural-network persistent-homology diagnostics, tracking
persistence-diagram distance between successive training states as a
validation-set-free correlate of generalization. Matters to the vault
because his method's specific design choice — building the simplicial
complex from every neuron and connection, with no subsampling step at all —
turned out to be structurally immune, by construction, to the hub-selection
sampling artifact the vault's Byzantine-trade-network study documents
elsewhere.

## References
- [[claim-gutierrez-fandino-2021-persistence-diagram-distance-tracks-generalization]] · [[claim-gutierrez-fandino-2021-method-subsamples-nothing-uses-full-network]]
- [[observation-persistent-homology-gradient-free-bridge-widrow-byzantine]] · [[observation-hub-selection-artifact-absent-by-design-in-founding-ph-generalization-papers]]
- [[entity-tolga-birdal]] · [[question-tda-neural-net-sampling-artifact-risk]]