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Improved Deep Neural Network Hardware-Accelerators Based on Non-Volatile-Memory: The Local Gains Technique., , , , , , , , , and 1 other author(s). ICRC, page 1-8. IEEE, (2017)Analytical modelling and leakage optimization in complementary resistive switch (CRS) crossbar arrays., , , and . ESSDERC, page 242-245. IEEE, (2014)Analog-to-Digital Conversion With Reconfigurable Function Mapping for Neural Networks Activation Function Acceleration., , , , , , and . IEEE J. Emerg. Sel. Topics Circuits Syst., 9 (2): 367-376 (2019)Neuromorphic devices and architectures for next-generation cognitive computing., , , , , , and . ISCAS, page 1-4. IEEE, (2017)Architectures and Circuits for Analog-memory-based Hardware Accelerators for Deep Neural Networks (Invited)., , , , , , , , , and 13 other author(s). ISCAS, page 1-5. IEEE, (2023)Optimization of Analog Accelerators for Deep Neural Networks Inference., , , , , , , , and . ISCAS, page 1-5. IEEE, (2020)Accelerating Deep Neural Networks with Analog Memory Devices., , , , , , , , and . AICAS, page 149-152. IEEE, (2020)Equivalent-accuracy accelerated neural-network training using analogue memory., , , , , , , , , and 4 other author(s). Nat., 558 (7708): 60-67 (2018)True Random Number Generation by Variability of Resistive Switching in Oxide-Based Devices., , , and . IEEE J. Emerg. Sel. Topics Circuits Syst., 5 (2): 214-221 (2015)Modeling of reliability and neuromorphic application of resistive switching devices.. Polytechnic University of Milan, Italy, (2016)