Estimating Post-Synaptic Effects for Online Training of Feed-Forward SNNs

Facilitating online learning in spiking neural networks (SNNs) is a key step in developing event-based models that can adapt to changing environments and learn from continuous data streams in real-time. Although forward-mode differentiation enables online learning, its computational requirements res...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	2024 International Conference on Neuromorphic Systems (ICONS) S. 264 - 271
Hauptverfasser:	Summe, Thomas M., Schaefer, Clemens JS, Joshi, Siddharth
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 30.07.2024
Schlagworte:	Adaptation models Approximation algorithms Computational modeling Encoding gradient approximation Neuromorphics online learning Real-time systems Scalability Spiking neural networks Streams Training
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!