SELF-SUPERVISED LEARNING METHODS FOR REPRESENTATION LEARNING AND ANOMALY DETECTION IN TIME SERIES: APPLICATIONS TO ASTRONOMY AND ELECTROENCEPHALOGRAPHY
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| Fecha de publicación: | 2022 |
| Objetivos: | The main objectives of this research proposal are to develop an information theoretic framework for self-supervised learning based methods for representation learning and anomaly detection in time-series, applied to astronomical light curves and electroencephalograms |
| Instrumento: | FONDECYT |
| Año de Inicio/Término: | 2022-2026 |
| Financiamiento/Sponsor: | CONICYT |
| Rol del Usuario: | INVESTIGADOR(A) RESPONSABLE |
| DOI: |
1220829 |