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DOCTOR: Dynamic On-Chip Remediation Against Temporally-Drifting Thermal Variations Toward Self-Corrected Photonic Tensor Accelerators
While off-chip noise-aware training and on-chip training have been proposed to enhance the variation tolerance of optical neural accelerators with moderate, static noises, we observe a notable performance degradation over time due to temporally drifting variations, which requires a real-time, in-situ calibration mechanism.
A Synchronized Layer-by-layer Growing Approach for Plausible Neuronal Morphology Generation
Neuronal morphology is essential for studying brain functioning and understanding neurodegenerative disorders.
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