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Generalized Key-Value Memory to Flexibly Adjust Redundancy in Memory-Augmented Networks., , , , and . IEEE Trans. Neural Networks Learn. Syst., 34 (12): 10993-10998 (December 2023)In-memory Vector Symbolic Architectures.. ETH Zurich, Zürich, Switzerland, (2023)base-search.net (ftethz:oai:www.research-collection.ethz.ch:20.500.11850/625319).TCNCA: Temporal Convolution Network with Chunked Attention for Scalable Sequence Processing., , , , , and . CoRR, (2023)Real-time Language Recognition using Hyperdimensional Computing on Phase-change Memory Array., , , , and . AICAS, page 1. IEEE, (2021)Architecting more than Moore: wireless plasticity for massive heterogeneous computer architectures (WiPLASH)., , , , , , , , , and 12 other author(s). CF, page 191-193. ACM, (2021)Wireless On-Chip Communications for Scalable In-memory Hyperdimensional Computing., , , , , and . CoRR, (2022)Generalized Key-Value Memory to Flexibly Adjust Redundancy in Memory-Augmented Networks., , , , and . CoRR, (2022)A 64-core mixed-signal in-memory compute chip based on phase-change memory for deep neural network inference., , , , , , , , , and 19 other author(s). CoRR, (2022)Mixed-precision deep learning based on computational memory., , , , , , , , , and 4 other author(s). CoRR, (2020)Deep learning acceleration based on in-memory computing., , , , , , , , , and 7 other author(s). IBM J. Res. Dev., 63 (6): 7:1-7:16 (2019)