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QGen: On the Ability to Generalize in Quantization Aware Training
In this work, we investigate the generalization properties of quantized neural networks, a characteristic that has received little attention despite its implications on model performance.
DeepliteRT: Computer Vision at the Edge
The proliferation of edge devices has unlocked unprecedented opportunities for deep learning model deployment in computer vision applications.
DeepGEMM: Accelerated Ultra Low-Precision Inference on CPU Architectures using Lookup Tables
A lot of recent progress has been made in ultra low-bit quantization, promising significant improvements in latency, memory footprint and energy consumption on edge devices.
Accelerating Deep Learning Model Inference on Arm CPUs with Ultra-Low Bit Quantization and Runtime
Deep Learning has been one of the most disruptive technological advancements in recent times.
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