Franz Scherr - Google Scholar Citations

Wolfgang MaassProfessor of Computer Science, Graz University of TechnologyVerified email at igi.tugraz.at
Robert LegensteinInstitute for Theoretical Computer Science, Graz University of TechnologyVerified email at igi.tugraz.at
Darjan SalajInstitute for Theoretical Computer Science, Graz University of Technology, AustriaVerified email at igi.tugraz.at
Guillaume BELLECTU GrazVerified email at igi.tugraz.at
Anand SubramoneyInstitute for Theoretical Computer Science, Graz University of Technology, AustriaVerified email at igi.tugraz.at
Karlheinz MeierRuprecht-Karls-Universität HeidelbergVerified email at kip.uni-heidelberg.de

Franz Scherr

Verified email at tugraz.at - Homepage


Title	Cited by	Year
Biologically inspired alternatives to backpropagation through time for learning in recurrent neural nets G Bellec, F Scherr, E Hajek, D Salaj, R Legenstein, W Maass arXiv preprint arXiv:1901.09049, 2019	10	2019
Neuromorphic Hardware learns to learn T Bohnstingl, F Scherr, C Pehle, K Meier, W Maass Frontiers in neuroscience 13, 2019	2	2019
Reservoirs learn to learn A Subramoney, F Scherr, W Maass arXiv preprint arXiv:1909.07486, 2019		2019
Eligibility traces provide a data-inspired alternative to backpropagation through time G Bellec, F Scherr, E Hajek, D Salaj, A Subramoney, R Legenstein, ...		2019
A solution to the learning dilemma for recurrent networks of spiking neurons G Bellec, F Scherr, A Subramoney, E Hajek, D Salaj, R Legenstein, ... bioRxiv, 738385, 2019		2019
Supplementary materials for: A solution to the learning dilemma for recurrent networks of spiking neurons G Bellec, F Scherr, A Subramoney, E Hajek, D Salaj, R Legenstein, ...
Biologically inspired alternatives to backpropagation through time for learning in recurrent neural networks G Bellec, F Scherr, D Salaj, E Hajek, R Legenstein, W Maass

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