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Fast and energy-efficient neuromorphic deep learning with first-spike times., , , , , , , , , and 2 other author(s). Nat. Mach. Intell., 3 (9): 823-835 (2021)Learning through structure: towards deep neuromorphic knowledge graph embeddings., , , and . CoRR, (2021)Live Demonstration: Versatile Emulation of Spiking Neural Networks on an Accelerated Neuromorphic Substrate., , , , , , , , , and 15 other author(s). ISCAS, page 1. IEEE, (2020)Machine learning on knowledge graphs for context-aware security monitoring., , and . CSR, page 55-60. IEEE, (2021)SpikE: spike-based embeddings for multi-relational graph data., and . IJCNN, page 1-8. IEEE, (2021)Neuromorphic Computing and Sensing in Space., , , , and . CoRR, (2022)Stochasticity from function - Why the Bayesian brain may need no noise., , , , , , , , and . Neural Networks, (2019)An energy-based model for neuro-symbolic reasoning on knowledge graphs., and . ICMLA, page 916-921. IEEE, (2021)Versatile Emulation of Spiking Neural Networks on an Accelerated Neuromorphic Substrate., , , , , , , , , and 15 other author(s). ISCAS, page 1-5. IEEE, (2020)Relational representation learning with spike trains.. IJCNN, page 1-8. IEEE, (2022)