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qtisas / qtisas
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Matthew Bryan / empyre
GNU General Public License v3.0 onlyElectron Microscopy Python Reconstruction, developed at the PGI-5 / ER-C - https://empyre.iffgit.fz-juelich.de/empyre/
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Workthrough of aiida-kkr tutorials at https://aiida-kkr.readthedocs.io
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Alexander Clausen / empyre
GNU General Public License v3.0 onlyElectron Microscopy Python Reconstruction, developed at the PGI-5 / ER-C
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Title: An introduction to training algorithms for neuromorphic computing and on-line learning Abstract: Training neural networks implemented in neuromorphic hardware is challenging due to the dynamic, sparse, and local nature of the computations. This tutorial will describe some established gradient-based solutions to address these challenges in the context of real-valued recurrent neural networks and spiking neural networks. Insights into gradient-based training algorithms and associated autodifferentiation methods lead to online synaptic plasticity rules and the necessary assumptions to implement them in in-memory computing devices. The tutorial will conclude with methods that can be used to improve and optimize learning algorithms using meta-learning and other meta-optimization approaches.
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