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Unveiling the Potential of Spiking Dynamics in Graph Representation Learning through Spatial-Temporal Normalization and Coding Strategies.

, , , , , , , and . CoRR, (2024)

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Towards Both Accurate and Robust Neural Networks Without Extra Data., and . ICANN (1), volume 13529 of Lecture Notes in Computer Science, page 379-390. Springer, (2022)Distributed Intelligent Collaborative Scheduling Mechanism for Cloud-Edge-End Resources in IoT., , , and . IAIC (3), page 56-68. (2023)Multiple service function chaining under load balance in SDN/NFV networks., , , , , and . PIMRC, page 1-6. IEEE, (2017)Bridging adversarial samples and adversarial networks., , , , and . CoRR, (2019)Minimizing transmission cost for multiple service function chains in SDN/NFV networks., , , , , and . PIMRC, page 1-6. IEEE, (2017)Unveiling the Potential of Spiking Dynamics in Graph Representation Learning through Spatial-Temporal Normalization and Coding Strategies., , , , , , , and . CoRR, (2024)Exploiting Spiking Dynamics with Spatial-temporal Feature Normalization in Graph Learning., , , , , and . IJCAI, page 3207-3213. ijcai.org, (2021)Neural Dynamics Pruning for Energy-Efficient Spiking Neural Networks., , , , and . ICME, page 1-6. IEEE, (2024)Endowing Spiking Neural Networks with Homeostatic Adaptivity for APS-DVS Bimodal Scenarios., , and . ICMI Companion, page 12-17. ACM, (2022)Optimized Service Function Path Scaling in SDN/NFV Networks., , , , and . ICSCC, page 27-32. ACM, (2019)