Spiking Neural networks as Universal Function Approximators - SNUFA 2021
Computational Neuroscience, Machine Learning, Mathematical Modeling and seminar by Prof Tara Hamilton, Dylan Muir, Katie Schumann, Henning Sprekeler
Hosted by Ad hoc
Tuesday 12:00–13:10 London (GMT+0)
Ended
Abstract
Like last year this online workshop brings together researchers in the field to present their work and discuss ways of translating these findings into a better understanding of neural circuits. Topics include artificial and biologically plausible learning algorithms and the dissection of trained spiking circuits toward understanding neural processing. We have a manageable number of talks with ample time for discussions.
This year’s executive committee comprises Chiara Bartolozzi, Sander Bohté, Dan Goodman, and Friedemann Zenke.
Topics
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- Video · 53 min · Nov 5, 2021Shirin Dora, Loughborough University
Unsupervised Spiking Neural Networks
Video · 45 min · Nov 2, 2021Tara Hamilton, University of Technology SydneyUniversal function approximation in balanced spiking networks through convex-concave boundary composition
Video · Nov 10, 2022W. F. Podlaski, Champalimaud
Conferences in Computational Neuroscience soon
All conferencesNeuroscience 2026
Nov 14–18, 2026Washington, United States