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RMP-Loss: Regularizing Membrane Potential Distribution for Spiking Neural Networks.

, , , , , , , and . ICCV, page 17345-17355. IEEE, (2023)

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NeuroCLIP: Neuromorphic Data Understanding by CLIP and SNN., , and . IEEE Signal Process. Lett., (2024)Membrane Potential Batch Normalization for Spiking Neural Networks., , , , , , , and . ICCV, page 19363-19373. IEEE, (2023)Deep Dive into Gradients: Better Optimization for 3D Object Detection with Gradient-Corrected IoU Supervision., , , , , , , and . CVPR, page 5136-5145. IEEE, (2023)RMP-Loss: Regularizing Membrane Potential Distribution for Spiking Neural Networks., , , , , , , and . ICCV, page 17345-17355. IEEE, (2023)Event Observation of Date-time Stamps for ADS Reconstruction., , and . ICACT, page 552-557. IEEE, (2019)Zero-shot sim-to-real transfer of reinforcement learning framework for robotics manipulation with demonstration and force feedback., , , , and . Robotica, 41 (3): 1015-1024 (March 2023)MyoChallenge 2022: Learning contact-rich manipulation using a musculoskeletal hand., , , , , , , , , and 19 other author(s). NeurIPS (Competition and Demos), volume 220 of Proceedings of Machine Learning Research, page 233-250. PMLR, (2021)Parametric modeling and comparative finite element analysis of spiral triangular strand and simple straight strand., , and . Adv. Eng. Softw., (2015)Safe multi-agent reinforcement learning for multi-robot control., , , , , , and . Artif. Intell., (June 2023)Towards Human-Level Bimanual Dexterous Manipulation with Reinforcement Learning., , , , , , , , , and . NeurIPS, (2022)