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Memristors for neural branch prediction: a case study in strict latency and write endurance challenges., , , , , , , and . Conf. Computing Frontiers, page 26:1-26:10. ACM, (2013)Improving Noise Tolerance of Mixed-Signal Neural Networks., , and . IJCNN, page 1-8. IEEE, (2019)Exponential-weight multilayer perceptron., , and . IJCNN, page 3709-3715. IEEE, (2017)3D-DPE: A 3D high-bandwidth dot-product engine for high-performance neuromorphic computing., , , and . DATE, page 1257-1260. IEEE, (2017)Mixed-Signal Vector-by-Matrix Multiplier Circuits Based on 3D-NAND Memories for Neurocomputing., , , and . DATE, page 696-701. IEEE, (2020)HO-FPIA: High-Order Field-Programmable Ising Arrays with In-Memory Computing., , , and . ISVLSI, page 252-259. IEEE, (2024)Redesigning Commercial Floating-Gate Memory for Analog Computing Applications., , , , , and . CoRR, (2014)Self-Adaptive Spike-Time-Dependent Plasticity of Metal-Oxide Memristors., , , , and . CoRR, (2015)Memristor-based perceptron classifier: Increasing complexity and coping with imperfect hardware., , , , and . ICCAD, page 549-554. IEEE, (2017)Efficient training algorithms for neural networks based on memristive crossbar circuits., , , and . IJCNN, page 1-8. IEEE, (2015)