ACIQ: Analytical Clipping for Integer Quantization of neural networks. - Ron Banner; Yury Nahshan; Elad Hoffer; Daniel Soudry (CoRR, 2018)

Post training 4-bit quantization of convolutional networks for rapid-deployment. - Ron Banner; Yury Nahshan; Daniel Soudry (NeurIPS, 2019)

Robust Quantization: One Model to Rule Them All. - Moran Shkolnik; Brian Chmiel; Ron Banner; Gil Shomron; Yury Nahshan; Alex M. Bronstein; Uri C. Weiser (NeurIPS, 2020)

Improving Post Training Neural Quantization: Layer-wise Calibration and Integer Programming. - Itay Hubara; Yury Nahshan; Yair Hanani; Ron Banner; Daniel Soudry (CoRR, 2020)

Accurate Post Training Quantization With Small Calibration Sets. - Itay Hubara; Yury Nahshan; Yair Hanani; Ron Banner; Daniel Soudry (ICML, 2021)

Loss aware post-training quantization. - Yury Nahshan; Brian Chmiel; Chaim Baskin; Evgenii Zheltonozhskii; Ron Banner; Alex M. Bronstein; Avi Mendelson (Mach. Learn., 2021)

Rotation Invariant Quantization for Model Compression. - Joseph Kampeas; Yury Nahshan; Hanoch Kremer; Gil Lederman; Shira Zaloshinski; Zheng Li; Emir Haleva (CoRR, 2023)

Linear Log-Normal Attention with Unbiased Concentration. - Yury Nahshan; Joseph Kampeas; Emir Haleva (ICLR, 2024)