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
Lukas Tuggener
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