106 citations · 174 across the 4 of their papers we have counts for
4 papers
Efficient non-uniform quantizer for quantized neural network targeting reconfigurable hardware
Natan Liss, Chaim Baskin, Avi Mendelson +2
Convolutional Neural Networks (CNN) has become more popular choice for various tasks such as computer vision, speech recognition and natural language processing. Thanks to their la…
NICE: Noise Injection and Clamping Estimation for Neural Network Quantization
Chaim Baskin, Natan Liss, Yoav Chai +5
Convolutional Neural Networks (CNN) are very popular in many fields including computer vision, speech recognition, natural language processing, to name a few. Though deep learning…
UNIQ: Uniform Noise Injection for Non-Uniform Quantization of Neural Networks
Chaim Baskin, Eli Schwartz, Evgenii Zheltonozhskii +4
We present a novel method for neural network quantization that emulates a non-uniform -quantile quantizer, which adapts to the distribution of the quantized parameters. Our appr…
Streaming Architecture for Large-Scale Quantized Neural Networks on an FPGA-Based Dataflow Platform
Chaim Baskin, Natan Liss, Evgenii Zheltonozhskii +2
Deep neural networks (DNNs) are used by different applications that are executed on a range of computer architectures, from IoT devices to supercomputers. The footprint of these ne…