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Understanding How Orthogonality of Parameters Improves Quantization of Neural Networks., and . IEEE Trans. Neural Networks Learn. Syst., 34 (12): 10737-10746 (December 2023)Edge AI without Compromise: Efficient, Versatile and Accurate Neurocomputing in Resistive Random-Access Memory., , , , , , , , , and 4 other author(s). CoRR, (2021)Opportunities for Analog Coding in Emerging Memory Systems., , , , , , , and . CoRR, (2017)Supervised classification-based stock prediction and portfolio optimization., , and . CoRR, (2014)FastDimeNet++: Training DimeNet++ in 22 minutes., , , , , , , , , and 4 other author(s). ICPP, page 274-284. ACM, (2023)Experimental Demonstration of Array-level Learning with Phase Change Synaptic Devices., , , , , , and . CoRR, (2014)Device and System Level Design Considerations for Analog-Non-Volatile-Memory Based Neuromorphic Architectures., , , and . CoRR, (2015)A compute-in-memory chip based on resistive random-access memory., , , , , , , , , and 4 other author(s). Nat., 608 (7923): 504-512 (2022)33.1 A 74 TMACS/W CMOS-RRAM Neurosynaptic Core with Dynamically Reconfigurable Dataflow and In-situ Transposable Weights for Probabilistic Graphical Models., , , , , , , , , and 3 other author(s). ISSCC, page 498-500. IEEE, (2020)