Longitudinal Variational Autoencoder

Siddharth Ramchandran*, Gleb Tikhonov, Kalle Kujanpaa, Miika Koskinen, Harri Lahdesmaki

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

10 Lataukset (Pure)

Abstrakti

Longitudinal datasets measured repeatedly over time from individual subjects, arise in many biomedical, psychological, social, and other studies. A common approach to analyse high-dimensional data that contains missing values is to learn a low-dimensional representation using variational autoencoders (VAEs). However, standard VAEs assume that the learnt representations are i.i.d., and fail to capture the correlations between the data samples. We propose the Longitudinal VAE (L-VAE), that uses a multi-output additive Gaussian process (GP) prior to extend the VAE's capability to learn structured low-dimensional representations imposed by auxiliary covariate information, and derive a new KL divergence upper bound for such GPs. Our approach can simultaneously accommodate both time-varying shared and random effects, produce structured low-dimensional representations, disentangle effects of individual covariates or their interactions, and achieve highly accurate predictive performance. We compare our model against previous methods on synthetic as well as clinical datasets, and demonstrate the state-of-theart performance in data imputation, reconstruction, and long-term prediction tasks.

AlkuperäiskieliEnglanti
Otsikko24TH INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS (AISTATS)
ToimittajatA Banerjee, K Fukumizu
KustantajaMICROTOME PUBLISHING
Sivumäärä11
TilaJulkaistu - 2021
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaInternational Conference on Artificial Intelligence and Statistics - Virtual, Online
Kesto: 13 huhtik. 202115 huhtik. 2021
Konferenssinumero: 24

Julkaisusarja

NimiProceedings of Machine Learning Research
KustantajaMICROTOME PUBLISHING
Vuosikerta130
ISSN (painettu)2640-3498

Conference

ConferenceInternational Conference on Artificial Intelligence and Statistics
LyhennettäAISTATS
KaupunkiVirtual, Online
Ajanjakso13/04/202115/04/2021

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