| 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 | 34 | 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, 2020 | 27* | 2020 |
| Neuromorphic hardware learns to learn T Bohnstingl, F Scherr, C Pehle, K Meier, W Maass Frontiers in neuroscience 13, 483, 2019 | 14 | 2019 |
| Reservoirs learn to learn A Subramoney, F Scherr, W Maass arXiv preprint arXiv:1909.07486, 2019 | 3 | 2019 |
| Eligibility traces provide a data-inspired alternative to backpropagation through time G Bellec, F Scherr, E Hajek, D Salaj, A Subramoney, R Legenstein, ... | 2 | 2019 |
| One-shot learning with spiking neural networks F Scherr, C Stöckl, W Maass bioRxiv, 2020 | 1 | 2020 |
| Dimensionality and flexibility of learning in biological recurrent neural networks BA Richards, C Clopath, RP Costa, W Maass, LY Prince, A Ghosh, ... | | 2020 |
| Slow processes of neurons enable a biologically plausible approximation to policy gradient A Subramoney, G Bellec, F Scherr, A Subramoney, E Hajek, D Salaj, ... 33nd NeurIPS workshop, 2019 | | 2019 |
| Automated Security Proofs for Symmetric Ciphers F Scherr | | 2015 |
| Biologically inspired alternatives to backpropagation through time for learning in recurrent neural nets Download PDF G Bellec, F Scherr, E Hajek, D Salaj, R Legenstein, W Maass | | |
| Supplements for “One-shot learning with spiking neural networks” F Scherr, C Stöckl, W Maass | | |
| A solution to the learning dilemma for recurrent G Bellec, F Scherr, A Subramoney, E Hajek, D Salaj, R Legenstein, ... | | |
| Gradient-based optimization of AMEA parameters F Scherr | | |
| 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 | | |
Wolfgang MaassProfessor of Computer Science, Graz University of TechnologyVerified email at igi.tugraz.at
