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Editorial: Focus on algorithms for neuromorphic computing., , and . Neuromorph. Comput. Eng., 3 (3): 30402 (September 2023)NEAT: Non-linearity Aware Training for Accurate and Energy-Efficient Implementation of Neural Networks on 1T-1R Memristive Crossbars., , , and . CoRR, (2020)SwitchX- Gmin-Gmax Switching for Energy-Efficient and Robust Implementation of Binary Neural Networks on Memristive Xbars., and . CoRR, (2020)Optimizing Deeper Spiking Neural Networks for Dynamic Vision Sensing., and . Neural Networks, (2021)Efficiency-driven Hardware Optimization for Adversarially Robust Neural Networks., , and . DATE, page 884-889. IEEE, (2021)Examining and Mitigating the Impact of Crossbar Non-idealities for Accurate Implementation of Sparse Deep Neural Networks., , and . DATE, page 1119-1122. IEEE, (2022)Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-linear Activations., , , and . ECCV (29), volume 12374 of Lecture Notes in Computer Science, page 399-414. Springer, (2020)Energy-efficient and Robust Cumulative Training with Net2Net Transformation., and . IJCNN, page 1-7. IEEE, (2020)Staged Inference using Conditional Deep Learning for energy efficient real-time smart diagnosis., , , and . EMBC, page 78-81. IEEE, (2017)Activation Density Driven Efficient Pruning in Training., , and . ICPR, page 8929-8936. IEEE, (2020)