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Bridging the gap between software simulation and emulation on neuromorphic hardware: An investigation of causes, effects and compensation of network-level anomalies in a mixed-signal waferscale neuromorphic modeling platform.

, , , , , , , , , , , and . CoRR, (2014)

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Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate., , , , , , , , , and 15 other author(s). CoRR, (2019)Bridging the gap between software simulation and emulation on neuromorphic hardware: An investigation of causes, effects and compensation of network-level anomalies in a mixed-signal waferscale neuromorphic modeling platform., , , , , , , , , and 2 other author(s). CoRR, (2014)Robustness from structure: Inference with hierarchical spiking networks on analog neuromorphic hardware., , , , , and . IJCNN, page 2209-2216. IEEE, (2017)Stochasticity from function - Why the Bayesian brain may need no noise., , , , , , , , and . Neural Networks, (2019)Generative models on accelerated neuromorphic hardware., , , , , , , , , and 14 other author(s). CoRR, (2018)Fast and deep neuromorphic learning with time-to-first-spike coding., , , , , , , , , and 1 other author(s). CoRR, (2019)Pattern representation and recognition with accelerated analog neuromorphic systems., , , , , , , , , and 25 other author(s). CoRR, (2017)A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems., , , , , , , , , and 24 other author(s). Biol. Cybern., 104 (4-5): 263-296 (2011)Pattern representation and recognition with accelerated analog neuromorphic systems., , , , , , , , , and 26 other author(s). ISCAS, page 1-4. IEEE, (2017)Spiking neurons with short-term synaptic plasticity form superior generative networks., , , , , , , and . CoRR, (2017)