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Stochastic Computing for Low-Power and High-Speed Deep Learning on FPGA., and . ISCAS, page 1-5. IEEE, (2019)MemTorch: An Open-source Simulation Framework for Memristive Deep Learning Systems., , , and . Neurocomputing, (2022)Design Space Exploration of Dense and Sparse Mapping Schemes for RRAM Architectures., , , , , , and . ISCAS, page 1107-1111. IEEE, (2022)Modeling and simulating in-memory memristive deep learning systems: An overview of current efforts., , and . Array, (2022)Using the IBM Analog In-Memory Hardware Acceleration Kit for Neural Network Training and Inference., , , , , , , , , and 1 other author(s). CoRR, (2023)LionHeart: A Layer-based Mapping Framework for Heterogeneous Systems with Analog In-Memory Computing Tiles., , , , , , , , and . CoRR, (2024)Improving the Accuracy of Analog-Based In-Memory Computing Accelerators Post-Training., , , , , , and . CoRR, (2024)MemTorch: A Simulation Framework for Deep Memristive Cross-Bar Architectures., and . ISCAS, page 1-5. IEEE, (2020)Navigating Local Minima in Quantized Spiking Neural Networks., , , and . AICAS, page 352-355. IEEE, (2022)Toward A Formalized Approach for Spike Sorting Algorithms and Hardware Evaluation., , , , , and . MWSCAS, page 1-4. IEEE, (2022)