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Contrasting Advantages of Learning With Random Weights and Backpropagation in Non-Volatile Memory Neural Networks.

, , , , , , and . IEEE Access, (2019)

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OXRAM based ELM architecture for multi-class classification applications., , , and . IJCNN, page 1-8. IEEE, (2015)Exploring Memory-Oriented Design Optimization of Edge AI Hardware for Extended Reality Applications., , , , , and . IEEE Micro, 43 (6): 40-49 (November 2023)Methodology for Realizing VMM with Binary RRAM Arrays: Experimental Demonstration of Binarized-ADALINE using OxRAM Crossbar., , , , , , and . ISCAS, page 1-5. IEEE, (2020)Design Exploration of IoT centric Neural Inference Accelerators., and . ACM Great Lakes Symposium on VLSI, page 391-396. ACM, (2018)Design Exploration of Hybrid CMOS-OxRAM Deep Generative Architectures., and . CoRR, (2018)SLIM: Simultaneous Logic-in-Memory Computing Exploiting Bilayer Analog OxRAM Devices., , , , , and . CoRR, (2018)Neuromorphic hybrid RRAM-CMOS RBM architecture., , , , and . NVMTS, page 1-6. IEEE, (2015)Low-Power Hardware-Based Deep-Learning Diagnostics Support Case Study., , and . CoRR, (2022)Demonstration of SMT-reflow Immune and SCA-resilient PUF on 28nm RRAM device array., , , , , , , , , and 1 other author(s). IMW, page 1-4. IEEE, (2023)Design of an Optimized CMOS ELM Accelerator., , , and . VLSID, page 443-447. IEEE, (2019)