Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Carpov, Dmitri"'
Can meta-learning discover generic ways of processing time series (TS) from a diverse dataset so as to greatly improve generalization on new TS coming from different datasets? This work provides positive evidence to this using a broad meta-learning f
Externí odkaz:
http://arxiv.org/abs/2002.02887
We focus on solving the univariate times series point forecasting problem using deep learning. We propose a deep neural architecture based on backward and forward residual links and a very deep stack of fully-connected layers. The architecture has a
Externí odkaz:
http://arxiv.org/abs/1905.10437
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 35:9242-9250
Can meta-learning discover generic ways of processing time series (TS) from a diverse dataset so as to greatly improve generalization on new TS coming from different datasets? This work provides positive evidence to this using a broad meta-learning f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd2707103aab870a90cc51530a3dfd51
https://doi.org/10.1609/aaai.v35i10.17115
https://doi.org/10.1609/aaai.v35i10.17115
Autor:
Hinrichs, Nils, Roeschl, Tobias, Lanmueller, Pia, Balzer, Felix, Eickhoff, Carsten, O'Brien, Benjamin, Falk, Volkmar, Meyer, Alexander
Publikováno v:
PLoS Digital Health; 9/12/2024, Vol. 3 Issue 9, p1-18, 18p