This work provides the first systematic study of transferring direct-coded spiking neural networks to event-based representations while aiming to preserve accuracy and reduce energy use.
A survey of machine unlearning
2 Pith papers cite this work. Polarity classification is still indexing.
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AFU-IC decouples client unlearning from global federated training in medical imaging and adds server-side invariance calibration to prevent relearning of erased data.
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Direct-to-Event Spiking Neural Network Transfer
This work provides the first systematic study of transferring direct-coded spiking neural networks to event-based representations while aiming to preserve accuracy and reduce energy use.
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Asynchronous Federated Unlearning with Invariance Calibration for Medical Imaging
AFU-IC decouples client unlearning from global federated training in medical imaging and adds server-side invariance calibration to prevent relearning of erased data.