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Unsupervised learning of global factors in deep generative models

  • Published:2023-02 Issue: Volume:134 Page:109130
  • ISSN:0031-3203
  • Container-title:Pattern Recognition
  • language:en
  • Short-container-title:Pattern Recognition

Author:

Peis IgnacioORCID,Olmos Pablo M.,Artés-Rodríguez AntonioORCID

Funder

Ministry of Communications and Information, Singapore

Federación Española de Enfermedades Raras

Comunidad de Madrid

Horizon 2020

España Ministerio de Ciencia Innovación y Universidades

Gobierno de España Ministerio de Ciencia e Innovación

European Commission

Agencia Estatal de Investigación

European Research Council

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference38 articles.

1. Disentangling and learning robust representations with natural clustering;Antoran,2019

2. Seeing 3d chairs: exemplar part-based 2d-3d alignment using a large dataset of cad models;Aubry,2014

3. Fairness in Machine Learning;Barocas,2017

4. Learning representations of multivariate time series with missing data;Bianchi;Pattern Recognit.,2019

5. D. Bouchacourt, R. Tomioka, S. Nowozin, Multi-level variational autoencoder: Learning disentangled representations from grouped observations, in: Proceedings of the 30nd AAAI Conference on Artificial Intelligence, 2018.

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