Learning of deep spiking networks

We will discuss possibilities of supervised training of deep spiking architectures. In the context of spiking networks back propagation is not applicable. Therefore, alternative approaches have to be followed. The goal of the group is to come up with different alternatives. One possible approach is recently proposed "target propagation", which employs local update rule that can be implemented with backward connection.

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Day Time Location
Tue, 26.04.2016 15:30 - 16:30 meet in the lobby
Thu, 28.04.2016 15:00 - 16:00 Panorama Room
Sat, 30.04.2016 14:00 - 15:00 Panorama Room


Adam Arany
Jaak Simm


Adam Arany
Christopher Bennett
Lukas Cavigelli
Simon Davidson
Tobi Delbruck
Michael Hopkins
Giacomo Indiveri
Gengting Liu
Shih-Chii Liu
Bragi Lovetrue
Manu Nair
Guido Novati
Johannes Partzsch
Melika Payvand
Mihai Alexandru Petrovici
Francesca Puppo
Ole Richter
Yulia Sandamirskaya
Evangelos Stromatias
André van Schaik
Nikolaos Vasileiadis
Bernhard Vogginger
Borys Wrobel
Qi Xu