Practical data efficient deep learning trough contrastive self-supervised learning
Beschreibung
Deep Learning is the key building block of most modern AI systems, but its data hunger is a problem - especially from an applied perspective. The goal of this project is to enable data efficient practical deep learning by developing novel contrastive learning methods.
Eckdaten
Projektleitung
Projektpartner
Universität Zürich / Neural Learning and Intelligent Systems Group
Projektstatus
abgeschlossen, 09/2022 - 09/2023
Institut/Zentrum
Centre for Artificial Intelligence (CAI)
Drittmittelgeber
Öffentliche Hand (ohne Bund)
Projektvolumen
60'480 CHF
