Thanks for Nothing: Predicting Zero-Valued Activations with Lightweight Convolutional Neural Networks. - Gil Shomron; Ron Banner; Moran Shkolnik; Uri C. Weiser (ECCV (10), 2020)

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)

Neural gradients are lognormally distributed: understanding sparse and quantized training. - Brian Chmiel; Liad Ben-Uri; Moran Shkolnik; Elad Hoffer; Ron Banner; Daniel Soudry (CoRR, 2020)

Neural gradients are near-lognormal: improved quantized and sparse training. - Brian Chmiel; Liad Ben-Uri; Moran Shkolnik; Elad Hoffer; Ron Banner; Daniel Soudry (ICLR, 2021)

DropCompute: simple and more robust distributed synchronous training via compute variance reduction. - Niv Giladi; Shahar Gottlieb; Moran Shkolnik; Asaf Karnieli; Ron Banner; Elad Hoffer; Kfir Y. Levy; Daniel Soudry (NeurIPS, 2023)

EXAQ: Exponent Aware Quantization For LLMs Acceleration. - Moran Shkolnik; Maxim Fishman; Brian Chmiel; Hilla Ben-Yaacov; Ron Banner; Kfir Yehuda Levy (CoRR, 2024)