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Deep learning incorporating biologically inspired neural dynamics and in-memory computing.

, , , and . Nat. Mach. Intell., 2 (6): 325-336 (2020)

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Biologically Inspired Dynamics Enhance Deep Learning., , and . ERCIM News, (2021)Deep learning incorporating biologically inspired neural dynamics and in-memory computing., , , and . Nat. Mach. Intell., 2 (6): 325-336 (2020)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)Online Spatio-Temporal Learning in Deep Neural Networks., , , and . IEEE Trans. Neural Networks Learn. Syst., 34 (11): 8894-8908 (November 2023)Neuromorphic system with phase-change synapses for pattern learning and feature extraction., , , and . IJCNN, page 3724-3732. IEEE, (2017)Feature Learning Using Synaptic Competition in a Dynamically-Sized Neuromorphic Architecture., , , and . ICRC, page 1-7. IEEE, (2017)Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence., , , , , , , , , and 18 other author(s). CoRR, (2024)Neuromorphic Architecture With 1M Memristive Synapses for Detection of Weakly Correlated Inputs., , , , , and . IEEE Trans. Circuits Syst. II Express Briefs, 64-II (11): 1342-1346 (2017)Learning in Deep Neural Networks Using a Biologically Inspired Optimizer., , , , and . CoRR, (2021)Towards efficient end-to-end speech recognition with biologically-inspired neural networks., , , , , and . CoRR, (2021)