---
res:
  bibo_abstract:
  - "Neural models learn data representations that lie on low-dimensional manifolds,\r\nyet
    modeling the relation between these representational spaces is an ongoing challenge.
    By integrating spectral geometry principles into neural modeling, we show\r\nthat
    this problem can be better addressed in the functional domain, mitigating complexity,
    while enhancing interpretability and performances on downstream tasks.\r\nTo this
    end, we introduce a multi-purpose framework to the representation learning\r\ncommunity,
    which allows to: (i) compare different spaces in an interpretable way\r\nand measure
    their intrinsic similarity; (ii) find correspondences between them, both\r\nin
    unsupervised and weakly supervised settings, and (iii) to effectively transfer\r\nrepresentations
    between distinct spaces. We validate our framework on various\r\napplications,
    ranging from stitching to retrieval tasks, and on multiple modalities,\r\ndemonstrating
    that Latent Functional Maps can serve as a swiss-army knife for\r\nrepresentation
    alignment@eng"
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Marco
      foaf_name: Fumero, Marco
      foaf_surname: Fumero
      foaf_workInfoHomepage: http://www.librecat.org/personId=1c1593eb-393f-11ef-bb8e-ab4f1e979650
  - foaf_Person:
      foaf_givenName: Marco
      foaf_name: Pegoraro, Marco
      foaf_surname: Pegoraro
  - foaf_Person:
      foaf_givenName: Valentino
      foaf_name: Maiorca, Valentino
      foaf_surname: Maiorca
  - foaf_Person:
      foaf_givenName: Francesco
      foaf_name: Locatello, Francesco
      foaf_surname: Locatello
      foaf_workInfoHomepage: http://www.librecat.org/personId=26cfd52f-2483-11ee-8040-88983bcc06d4
    orcid: 0000-0002-4850-0683
  - foaf_Person:
      foaf_givenName: Emanuele
      foaf_name: Rodolà, Emanuele
      foaf_surname: Rodolà
  bibo_volume: 37
  dct_date: 2024^xs_gYear
  dct_isPartOf:
  - http://id.crossref.org/issn/1049-5258
  dct_language: eng
  dct_publisher: Neural Information Processing Systems Foundation@
  dct_title: 'Latent functional maps: A spectral framework for representation alignment@'
...