Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Farrell, Steve"'
Autor:
Ju, Xiangyang, Murnane, Daniel, Calafiura, Paolo, Choma, Nicholas, Conlon, Sean, Farrell, Steve, Xu, Yaoyuan, Spiropulu, Maria, Vlimant, Jean-Roch, Aurisano, Adam, Hewes, V, Cerati, Giuseppe, Gray, Lindsey, Klijnsma, Thomas, Kowalkowski, Jim, Atkinson, Markus, Neubauer, Mark, DeZoort, Gage, Thais, Savannah, Chauhan, Aditi, Schuy, Alex, Hsu, Shih-Chieh, Ballow, Alex, Lazar, and Alina
The Exa.TrkX project has applied geometric learning concepts such as metric learning and graph neural networks to HEP particle tracking. Exa.TrkX's tracking pipeline groups detector measurements to form track candidates and filters them. The pipeline
Externí odkaz:
http://arxiv.org/abs/2103.06995
Autor:
Hewes, V, Aurisano, Adam, Cerati, Giuseppe, Kowalkowski, Jim, Lee, Claire, Liao, Wei-keng, Day, Alexandra, Agrawal, Ankit, Spiropulu, Maria, Vlimant, Jean-Roch, Gray, Lindsey, Klijnsma, Thomas, Calafiura, Paolo, Conlon, Sean, Farrell, Steve, Ju, Xiangyang, Murnane, Daniel
This paper presents a graph neural network (GNN) technique for low-level reconstruction of neutrino interactions in a Liquid Argon Time Projection Chamber (LArTPC). GNNs are still a relatively novel technique, and have shown great promise for similar
Externí odkaz:
http://arxiv.org/abs/2103.06233
An image dataset of 10 different size molecules, where each molecule has 2,000 structural variants, is generated from the 2D cross-sectional projection of Molecular Dynamics trajectories. The purpose of this dataset is to provide a benchmark dataset
Externí odkaz:
http://arxiv.org/abs/1911.07644
Akademický článek
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Autor:
Hewes, Jeremy, Aurisano, Adam, Cerati, Giuseppe, Kowalkowski, Jim, Lee, Claire, Liao, Wei-keng, Day, Alexandra, Agrawal, Ankit, Spiropulu, Maria, Vlimant, Jean-Roch, Gray, Lindsey, Klijnsma, Thomas, Calafiura, Paolo, Conlon, Sean, Farrell, Steve, Ju, Xiangyang, Murnane, Daniel
Publikováno v:
EPJ Web of Conferences; 8/23/2021, Vol. 251, p1-7, 7p
Autor:
Farrell, Steve, Vose, Aaron, Evans, Oliver, Henderson, Matthew, Cholia, Shreyas, Pérez, Fernando, Bhimji, Wahid, Canon, Shane, Thomas, Rollin, Prabhat
Deep learning researchers are increasingly using Jupyter notebooks to implement interactive, reproducible workflows with embedded visualization, steering and documentation. Such solutions are typically deployed on small-scale (e.g. single server) com
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______325::c68d6d7d5166113ac55cdf00bb810564
https://escholarship.org/uc/item/79b9v6f9
https://escholarship.org/uc/item/79b9v6f9
Autor:
Bard, Debbie, Bhimji, Wahid, Paul, David, Lockwood, Glenn K, Wright, Nicholas J, Antypas, Katie, Prabhat, Prabhat, Farrell, Steve, Ovsyannikov, Andrey, Romanus, Melissa, Van Straalen, Brian, Trebotich, David, Weber, Guenter
Publikováno v:
Bard, Debbie; Bhimji, Wahid; Paul, David; Lockwood, Glenn K; Wright, Nicholas J; Antypas, Katie; et al.(2016). Experiences with the Burst Buffer at NERSC:. Lawrence Berkeley National Laboratory: Lawrence Berkeley National Laboratory. Retrieved from: http://www.escholarship.org/uc/item/3ws838j6
NVRAM-based Burst Buffers are an important part of the emerging HPC storage landscape. The National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory recently installed one of the first Burst Buffer systems
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______325::41f1c5886bba872f6cc3f9592cb76daf
http://www.escholarship.org/uc/item/3ws838j6
http://www.escholarship.org/uc/item/3ws838j6