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Beyond charge-based computation: Boolean and non-Boolean computing with spin torque devices., , , and . ISLPED, page 139-142. IEEE, (2013)Exploring Boolean and Non-Boolean Computing Applications of Spin Torque Devices., , , and . CoRR, (2013)Defend Deep Neural Networks Against Adversarial Examples via Fixed andDynamic Quantized Activation Functions., , , and . CoRR, (2018)Ultra-low Energy, High-Performance Dynamic Resistive Threshold Logic., , and . CoRR, (2013)Processing-In-Memory Acceleration of Convolutional Neural Networks for Energy-Effciency, and Power-Intermittency Resilience., , , and . ISQED, page 8-13. IEEE, (2019)Defense-Net: Defend Against a Wide Range of Adversarial Attacks through Adversarial Detector., and . ISVLSI, page 332-337. IEEE, (2019)Ultra low power associative computing with spin neurons and resistive crossbar memory., , and . DAC, page 107:1-107:6. ACM, (2013)Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness against Adversarial Attack., , and . CoRR, (2018)Representable Matrices: Enabling High Accuracy Analog Computation for Inference of DNNs using Memristors., , , and . CoRR, (2019)Optimize Deep Convolutional Neural Network with Ternarized Weights and High Accuracy., , and . WACV, page 913-921. IEEE, (2019)