StatQAT: Statistical Quantizer Optimization for Deep Networks

ArXi:2605.17745v1 Announce Type: cross Quantization is essential for reducing the computational cost and memory usage of deep neural networks, enabling efficient inference on low-precision hardware. Despite the growing adoption of uniform and floating-point quantization schemes, selecting optimal quantization parameters remains a key challenge, particularly for diverse data distributions encountered during