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pro vyhledávání: '"Raquel, Aoki"'
This work proposes the M3E2, a multi-task learning neural network model to estimate the effect of multiple treatments. In contrast to existing methods, M3E2 can handle multiple treatment effects applied simultaneously to the same unit, continuous and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53237b0fabbed9da744e4173688fb617
Predicting multiple heterogeneous biological and medical targets is a challenge for traditional deep learning models. In contrast to single-task learning, in which a separate model is trained for each target, multi-task learning (MTL) optimizes a sin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b59665bcc447daffa316ce87600381c7