We are delighted to announce the finalised program for the SNUFA22 spiking 
neural network workshop. It's free to attend but you do need to register in 
advance:

http://snufa.net/2022/

9-10 November 2022, European afternoons. (Subscribe to the Google 
Calendar<https://calendar.google.com/calendar/u/0?cid=OTYzMGJmOWIyZmJjZjNmNjE0ZDMzN2MyZTVmZjhmMWQ0NDYxZTMwYTM3OWNlNmJmZDA5YWVkMzg1MGJlN2IxMUBncm91cC5jYWxlbmRhci5nb29nbGUuY29t>.)

Invited speakers.

  *   Charlotte Frenkel<https://chfrenkel.github.io/> (TU Delft)
  *   Priya Panda<https://intelligentcomputinglab.yale.edu/> (Yale)
  *   Yiota Poirazi<http://dendrites.gr/> (Institute of Molecular Biology and 
Biotechnology IMBB)
  *   Yonghong Tian<https://www.pkuml.org/> (Peking University)

Contributed talks:

Thomas Limbacher, Ozan Özdenizci, Robert Legenstein (TU Graz)
Memory-enriched computation and learning in spiking neural networks through 
Hebbian plasticity

M. Nardin, J. W. Phillips, W. F. Podlaski, S. W. Keemink (IST Austria)
Nonlinear computations in spiking neural networks through multiplicative 
synapses

A. Subramoney, K. K. Nazeer, M. Schöne, C. Mayr, D. Kappel (University of 
Bochum)
Beyond Biologically Plausible Spiking Networks for Neuromorphic Computing

A. Galloni, A. Peddada, A. Milstein (Rutgers)
Behavioral Timescale Synaptic Plasticity (BTSP) for biologically plausible 
credit assignment across multiple layers via top-down gating of dendritic 
plasticity

W. F. Podlaski, C. K. Machens (Champalimaud)
Universal function approximation in balanced spiking networks through 
convex-concave boundary composition

B. Yin, F. Corradi, and S. M. Bohte (CWI)
Training Dynamic Spiking Neural Network via Forward Propagation Through Time

Z. Liao, D. Hadjiabadi, S. Terada, I. Soltesz, A. Losonczy (Columbia)
A biologically plausible inhibitory plasticity rule for world-model learning in 
SNNs

C. B. Currin, K. Stecher, C. Pfeffer, G. Novarino, and T. P. Vogels (IST 
Austria)
Bridging the gap between artificial models and cortical circuits

Plus around 30 posters.

Many thanks!
Dan Goodman, Friedemann Zenke, Katie Schuman, Tim Masquelier

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