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CERN Document Server 2,019 εγγραφές βρέθηκαν  1 - 10επόμενοτέλος  μετάβαση στην εγγραφή: Η έρευνα πήρε 0.46 δευτερόλεπτα. 
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Parameter Estimation with Neural Simulation-Based Inference in ATLAS / Coelho Lopes De Sa, Rafael (University of Massachusetts (US)) ; Ghosh, Aishik (University of California Irvine (US)) ; Louppe, Gilles Claude ; Martinez Outschoorn, Verena Ingrid (University of Massachusetts (US)) ; Maury, Arnaud Jean (Université Paris-Saclay (FR)) ; Rousseau, David (Université Paris-Saclay (FR)) ; Sandesara, Jay Ajitbhai (University of Massachusetts (US)) ; Schaffer, R D (Université Paris-Saclay (FR)) ; Whiteson, Daniel (University of California Irvine (US)) /ATLAS Collaboration
Neural Simulation-Based Inference (NSBI) is a powerful class of machine learning (ML)-based methods for statistical inference that naturally handle high dimensional parameter estimation without the need to bin data into low-dimensional summary histograms. Such methods are promising for a range of measurements at the Large Hadron Collider, where no single observable may be optimal to scan over the entire theoretical phase space under consideration, or where binning data into histograms could result in a loss of sensitivity. [...]
ATL-PHYS-SLIDE-2024-566.- Geneva : CERN, 2024 - 41 p. Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
In : ML4Jets2024, Paris, Fr, 4 - 8 Nov 2024
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Parameter Estimation in ATLAS with Neural Simulation-Based Inference / Ghosh, Aishik (University of California Irvine (US)) /ATLAS Collaboration
Neural Simulation-Based Inference (NSBI) is a powerful class of machine learning (ML)-based methods for statistical inference that naturally handle high dimensional parameter estimation without the need to bin data into low-dimensional summary histograms. Such methods are promising for a range of measurements at the Large Hadron Collider, where no single observable may be optimal to scan over the entire theoretical phase space under consideration, or where binning data into histograms could result in a loss of sensitivity. [...]
ATL-SOFT-SLIDE-2024-508.- Geneva : CERN, 2024 Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
In : 27th International Conference on Computing in High Energy & Nuclear Physics, Kraków, Pl, 19 - 25 Oct 2024
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Flavour Physics review / Wormser, Guy Henri Maurice (Université Paris-Saclay (FR))
LHCb-TALK-2020-015.- Geneva : CERN, 2020 Fulltext: PDF;
In : Lake Louise Winter Institute 2020, Chateau Lake Louise, Canada, 9 - 15 Feb 2020
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Overcoming challenges of quantum interference at LHC with neural simulation-based inference and a full implementation in ATLAS / Ghosh, Aishik (University of California Irvine (US)) /ATLAS Collaboration
Quantum interference between signal and background Feynman diagrams produce non-linear effects that challenge core assumptions going into the statistical analysis methodology in particle physics. I show that for such cases, no single observable can capture all the relevant information needed to perform optimal inference of theory parameters from data collected in our experiments. [...]
ATL-SOFT-SLIDE-2024-613.- Geneva : CERN, 2024 Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
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ATLAS Data Analysis using a Parallel Workflow on Distributed Cloud-based Services with GPUs / Sandesara, Jay Ajitbhai (Amherst College (US)) ; Coelho Lopes De Sa, Rafael (University of Massachusetts (US)) ; Martinez Outschoorn, Verena Ingrid (University of Massachusetts (US)) ; Barreiro Megino, Fernando Harald (University of Texas at Arlington (US)) ; Elmsheuser, Johannes (Brookhaven National Laboratory (US)) ; Klimentov, Alexei (Brookhaven National Laboratory (US))
A new type of parallel workflow is developed for the ATLAS experiment at the Large Hadron Collider, that makes use of distributed computing combined with a cloud-based infrastructure. [...]
ATL-SOFT-PROC-2023-023. - 2024 - 8.
Original Communication (restricted to ATLAS) - Full text
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Lepton Universality tests in EW penguin decays at LHCb / Marin Benito, Carla (Université Paris-Saclay (FR))
LHCb-TALK-2020-135.- Geneva : CERN, 2020 Fulltext: PDF;
In : 40th International Conference on High Energy Physics, Prague, Czech Republic, 28 Jul - 6 Aug 2020
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Lepton Flavour Universality: LHCb results and prospects / Wormser, Guy Henri Maurice (Université Paris-Saclay (FR))
LHCb-TALK-2020-081.- Geneva : CERN, 2020 Fulltext: PDF;
In : Dark Matter @ LHC 2020, Hamburg, Germany, 2 - 5 Jun 2020
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ATLAS data analysis using a parallelized workflow on distributed cloud-based services with GPUs / Sandesara, Jay Ajitbhai (Amherst College (US)) ; Coelho Lopes De Sa, Rafael (University of Massachusetts (US)) ; Martinez Outschoorn, Verena Ingrid (University of Massachusetts (US)) ; Barreiro Megino, Fernando Harald (University of Texas at Arlington (US)) ; Elmsheuser, Johannes (Brookhaven National Laboratory (US)) ; Klimentov, Alexei (Brookhaven National Laboratory (US)) /ATLAS Collaboration
We present a new implementation of simulation-based inference using data collected by the ATLAS experiment at the LHC. The method relies on large ensembles of deep neural networks to approximate the exact likelihood. [...]
ATL-SOFT-SLIDE-2023-169.- Geneva : CERN, 2023 Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
In : 26th International Conference on Computing in High Energy & Nuclear Physics, Norfolk, Virginia, Us, 8 - 12 May 2023
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(27)
Not yet available
 Overcoming challenges of quantum interference at LHC with neural simulation-based inference and a full implementation in ATLAS / Ghosh, Aishik (speaker) (University of California Irvine (US))
Quantum interference between signal and background Feynman diagrams produce non-linear effects that challenge core assumptions going into the statistical analysis methodology in particle physics. I show that for such cases, no single observable can capture all the relevant information needed to perform optimal inference of theory parameters from data collected in our experiments. [...]
2024 - 3333. EP-IT Data Science Seminars External link: Event details In : Overcoming challenges of quantum interference at LHC with neural simulation-based inference and a full implementation in ATLAS
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PRODUCTION OF HEAVY QUARKONIA AT LHCb / Zhovkovska, Valeriia (Université Paris-Saclay (FR))
LHCb-TALK-2021-023.- Geneva : CERN, 2021 Fulltext: PDF;
In : The 14th International Workshop on Heavy Quarkonium, Online, Online, 15 - 19 Mar 2021
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