4 citations · 7 across the 5 of their papers we have counts for
3 papers · 1 filter
FIT: A Metric for Model Sensitivity
Ben Zandonati, Adrian Alan Pol, Maurizio Pierini +2
Model compression is vital to the deployment of deep learning on edge devices. Low precision representations, achieved via quantization of weights and activations, can reduce infer…
AMED: Automatic Mixed-Precision Quantization for Edge Devices
Moshe Kimhi, Tal Rozen, Avi Mendelson +1
Quantized neural networks are well known for reducing the latency, power consumption, and model size without significant harm to the performance. This makes them highly appropriate…
Lightweight Jet Reconstruction and Identification as an Object Detection Task
Adrian Alan Pol, Thea Aarrestad, Ekaterina Govorkova +8
We apply object detection techniques based on deep convolutional blocks to end-to-end jet identification and reconstruction tasks encountered at the CERN Large Hadron Collider (LHC…