Wolfgang Maass

Technische Universität Graz, Graz, Steiermark, Austria 
computation & theory
"Wolfgang Maass"
Mean distance: 14.5 (cluster 17)
Cross-listing: Computational Biology Tree


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Kurt Schütte grad student


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Prashant Joshi grad student TU Graz
Stefan Klampfl grad student TU Graz
Malte J. Rasch grad student 2004-2008 TU Graz
Michael Pfeiffer grad student 2003-2010 TU Graz
Bernhard Nessler grad student 2006-2013 TU Graz


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Rui Ponte Costa collaborator 2011-2013 Edinburgh
BETA: Related publications


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Zenke F, Bohté SM, Clopath C, et al. (2021) Visualizing a joint future of neuroscience and neuromorphic engineering. Neuron. 109: 571-575
Bellec G, Scherr F, Subramoney A, et al. (2020) A solution to the learning dilemma for recurrent networks of spiking neurons. Nature Communications. 11: 3625
Papadimitriou CH, Vempala SS, Mitropolsky D, et al. (2020) Brain computation by assemblies of neurons. Proceedings of the National Academy of Sciences of the United States of America
Müller MG, Papadimitriou CH, Maass W, et al. (2020) A model for structured information representation in neural networks of the brain. Eneuro
Kaiser J, Hoff M, Konle A, et al. (2019) Embodied Synaptic Plasticity With Online Reinforcement Learning. Frontiers in Neurorobotics. 13: 81
Pokorny C, Ison MJ, Rao A, et al. (2019) STDP Forms Associations between Memory Traces in Networks of Spiking Neurons. Cerebral Cortex (New York, N.Y. : 1991)
Bohnstingl T, Scherr F, Pehle C, et al. (2019) Neuromorphic Hardware Learns to Learn. Frontiers in Neuroscience. 13: 483
Yan Y, Kappel D, Neumaerker F, et al. (2019) Efficient Reward-Based Structural Plasticity on a SpiNNaker 2 Prototype. Ieee Transactions On Biomedical Circuits and Systems
Liu C, Bellec G, Vogginger B, et al. (2018) Memory-Efficient Deep Learning on a SpiNNaker 2 Prototype. Frontiers in Neuroscience. 12: 840
Kappel D, Legenstein R, Habenschuss S, et al. (2018) A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning. Eneuro. 5
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