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SNUFA 2021

Like last year this online workshop brings together researchers in the fields of computational neuroscience, machine learning, and neuromorphic engineering 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 comprised Chiara Bartolozzi, Sander Bohté, Dan Goodman, and Friedemann Zenke.

The workshop took place 2-3 November, 2021.

Thanks to World Wide Neuro for sponsoring this event!


Talks can be viewed on Crowdcast or YouTube.


List of abstracts

Time (CET) Session Local date/time
November 2nd    
14:00 Welcome by the organizers
  Session 1 (Chair: Chiara Bartolozzi)  
14:10 Tara Hamilton, University of Technology Sydney, Australia (invited talk)
Unsupervised Spiking Neural Networks
14:55 Dominik Dold, ESA ESTEC, Germany
Spike-based embeddings for multi-relational graph data
15:15 Ulysse Rancon, U Bordeaux, France
StereoSpike: Depth Learning with a Spiking Neural Network
15:35 Break (30mins)  
  Session 2 (Chair: Friedemann Zenke)  
16:05 Henning Sprekeler, TU Berlin, Germany (invited talk)
Optimising spiking interneuron circuits for compartment-specific feedback inhibition
16:50 Viola Priesemann, MPI-DS, Germany
Deriving local synaptic learning rules for efficient representations in networks of spiking neurons
17:10 Nicolas Perez-Nieves, Imperial
Understanding the role of neural heterogeneity in learning
17:30 Break (30mins)
18:00 Panel debate (Zoom)
November 3rd    
14:00 Welcome
  Session 3 (Chair: Sander Bohte)  
14:10 Dylan Muir, SynSense, Switzerland (invited talk)
Machine Learning with SNNs, for low-power inference on neuromorphic hardware
14:55 Julia Gygax, FMI, Switzerland
Optimal initialization strategies for Deep Spiking Neural Networks
15:15 Christian Pehle, Uni Heidelberg, Germany
Event-based Backpropagation for Exact Gradients in Spiking Neural Networks
15:35 Break (15mins)
15:50 Poster session (40mins)
In individual Zoom rooms
  Session 4 (Chair: Dan Goodman)  
16:30 Catherine Schuman, Oak Ridge National Laboratory, USA (invited talk)
Evolutionary Optimization for Spiking Neural Networks and Neuromorphic Computing
17:15 James Knight, University of Sussex, UK
Efficient GPU training of SNNs using approximate RTRL
17:35 Jens Egholm Pedersen, KTH, Sweden
Norse: A library for gradient-based learning in Spiking Neural Networks
17:55 Closing remarks by organizers


Last year’s workshop

You can read last year’s meeting report here, watch last year’s talks and discussions on Crowdcast or YouTube.