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cs.LG2026
Spike-Aware Gradient-Based Mixed-Precision Quantization of Spiking Neural Networks for Vision Applications
Rajshekhar Rakshit, Devgokul B., Rakshitha Kalkura +1
In recent years, Spiking Neural Networks (SNNs) have gained massive attention as an energy-efficient neural computing paradigm due to their event-driven and sparse computing capabi…
cs.LG2024
QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities
Sai Kiran Narayanaswami, Gopalakrishnan Srinivasan, Balaraman Ravindran
As machine learning gets deployed more and more widely, and model sizes continue to grow, improving computational efficiency during model inference has become a key challenge. In m…