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Dot-product engine as computing memory to accelerate machine learning algorithms., , , and . ISQED, page 374-379. IEEE, (2016)Physics-based memristor models., , and . ISCAS, page 217-220. IEEE, (2013)PANTHER: A Programmable Architecture for Neural Network Training Harnessing Energy-efficient ReRAM., , , , , , , , , and . CoRR, (2019)Regular Expression Matching with Memristor TCAMs., , , , , , , , , and 2 other author(s). ICRC, page 1-11. IEEE, (2018)Integration of Physics-Derived Memristor Models with Machine Learning Frameworks., , , and . CoRR, (2024)Looking Ahead for Resistive Memory Technology: A broad perspective on ReRAM technology for future storage and computing., , , , and . IEEE Consumer Electron. Mag., 6 (1): 94-103 (2017)Non-idealities and Design Solutions for Analog Memristor-Based Content-Addressable Memories., , , and . NANOARCH, page 17:1-17:6. ACM, (2023)Prospects for Analog Circuits in Deep Networks., , and . CoRR, (2021)Computing High-Degree Polynomial Gradients in Memory., , , , , , , , and . CoRR, (2024)Local Fading Memory Effects in a Tantalum Oxide ReRAM Cell from Hewlett Packard Labs., , , , , , and . MetroXRAINE, page 971-976. IEEE, (2023)