Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Sirkin Olya"'
Autor:
Pol Adrian Alan, Aarrestad Thea, Govorkova Katya, Halily Roi, Kopetz Tal, Klempner Anat, Loncar Vladimir, Ngadiuba Jennifer, Pierini Maurizio, Sirkin Olya, Summers Sioni
Publikováno v:
EPJ Web of Conferences, Vol 251, p 04027 (2021)
We apply object detection techniques based on Convolutional Neural Networks to jet reconstruction and identification at the CERN Large Hadron Collider. In particular, we focus on CaloJet reconstruction, representing each event as an image composed of
Externí odkaz:
https://doaj.org/article/cdaa8b5f1b46459e8e7aac20a08d5b03
Autor:
Zandonati, Ben, Bucagu, Glenn, Pol, Adrian Alan, Pierini, Maurizio, Sirkin, Olya, Kopetz, Tal
Model compression is instrumental in optimizing deep neural network inference on resource-constrained hardware. The prevailing methods for network compression, namely quantization and pruning, have been shown to enhance efficiency at the cost of perf
Externí odkaz:
http://arxiv.org/abs/2302.07612
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 inference time and memory requirements. However, quantifying and predicting
Externí odkaz:
http://arxiv.org/abs/2210.08502
Autor:
Pol, Adrian Alan, Aarrestad, Thea, Govorkova, Ekaterina, Halily, Roi, Klempner, Anat, Kopetz, Tal, Loncar, Vladimir, Ngadiuba, Jennifer, Pierini, Maurizio, Sirkin, Olya, Summers, Sioni
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). Collision events produced at the LHC and represented as an image co
Externí odkaz:
http://arxiv.org/abs/2202.04499
Quantized neural networks are well known for reducing latency, power consumption, and model size without significant degradation in accuracy, making them highly applicable for systems with limited resources and low power requirements. Mixed precision
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::814a9366fcac1aa4b5622a76bb19a6c5
http://arxiv.org/abs/2205.15437
http://arxiv.org/abs/2205.15437