2 citations · 3 across the 9 of their papers we have counts for
6 papers · 1 filter
Bayesian Rain Field Reconstruction using Commercial Microwave Links and Diffusion Model Priors
Badr Moufad, Albina Ilina, Hai Victor Habi +4
Commercial Microwave Links (CMLs) offer dense spatial coverage for rainfall sensing but produce path-integrated measurements that make accurate ground-level reconstruction challeng…
LATMiX: Learnable Affine Transformations for Microscaling Quantization of LLMs
Ofir Gordon, Lior Dikstein, Arnon Netzer +2
Post-training quantization (PTQ) is a widely used approach for reducing the memory and compute costs of large language models (LLMs). Recent studies have shown that applying invert…
TabGRU: An Enhanced Design for Urban Rainfall Intensity Estimation Using Commercial Microwave Links
Xingwang Li, Mengyun Chen, Jiamou Liu +8
In the face of accelerating global urbanization and the increasing frequency of extreme weather events, highresolution urban rainfall monitoring is crucial for building resilient s…
MLoRQ: Bridging Low-Rank and Quantization for Transformer Compression
Ofir Gordon, Ariel Lapid, Elad Cohen +3
Deploying transformer-based neural networks on resource-constrained edge devices presents a significant challenge. This challenge is often addressed through various techniques, suc…
Data Generation for Hardware-Friendly Post-Training Quantization
Lior Dikstein, Ariel Lapid, Arnon Netzer +1
Zero-shot quantization (ZSQ) using synthetic data is a key approach for post-training quantization (PTQ) under privacy and security constraints. However, existing data generation m…
HMQ: Hardware Friendly Mixed Precision Quantization Block for CNNs
Hai Victor Habi, Roy H. Jennings, Arnon Netzer
Recent work in network quantization produced state-of-the-art results using mixed precision quantization. An imperative requirement for many efficient edge device hardware implemen…