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 comprises Chiara Bartolozzi, Sander Bohté, Dan Goodman, and Friedemann Zenke.
The workshop will take place 2-3 November, 2021 (please note change of date from original announcement).
Abstract submission will close 1 October, 2021. Acceptance notification expected by 18th of October, 2021.
Registration and submissions
Registration is free. Click here to register.
Abstract submission is now closed.
List of abstracts
|Time (CET)||Session||Local date/time|
|14:00||Welcome by the organizers|
|Session 1 (Chair: Chiara Bartolozzi)|
|14:10||Tara Hamilton, University of Technology Sydney, Australia (invited talk)|
|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
|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
|18:00||Panel debate (Zoom)|
|Session 3 (Chair: Sander Bohte)|
|14:10||Dylan Muir, SynSense, Switzerland (invited talk)|
|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
|15:50||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|
- Two half days (CEST afternoons)
- 4 invited talks
- 8 contributed talks
- Poster session
- Panel debate: “What should be the next big breakthrough in spiking neural networks?” (speakers to be decided)
Last year’s workshop
You can read last year’s meeting report here, watch last year’s talks and discussions on Crowdcast or YouTube.