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CERN Document Server 2,005 records found  1 - 10próximoend  jump to record: Search took 0.48 seconds. 
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 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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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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3.
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An implementation of Neural Simulation-Based Inference for Parameter Estimation in ATLAS
Neural Simulation-Based Inference (NSBI) is a powerful class of machine learning (ML)-based methods for statistical inference that naturally handles high-dimensional parameter estimation without the need to bin data into low-dimensional summary histograms. [...]
ATLAS-CONF-2024-015. - 2024 - mult..
Original Communication (restricted to ATLAS) - Full text
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4.
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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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5.
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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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6. Recommendations of the Finance Committee to Council as to the Financing of the 1965 Supplementary Programme
Recommandations du Comité des Finances au Conseil au sujet du financement du programme supplémentaire pour 1965
CERN/0572
28th Session of Council ; 1964
English: PDF
French: PDF
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7. Expenditure in Excess of Provisions
Dépassements de crédits
CERN/FC/0726/Add.
64th Meeting of Finance Committee ; 1964
English: PDF
French: PDF
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8. List of Participants
Liste des participants
CERN/FC/0740
64th Meeting of Finance Committee ; 1964
English: PDF
French: PDF
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9. Financing of 1965 Supplementary Programme
CERN/FC/0742
64th Meeting of Finance Committee ; 1964
English: PDF
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10. Draft Agreements Concerning the Site Leased to CERN on French Territory - Drafts Letter of Interpretation and Acknowledgement of Receipt
Projets d'accords relatifs au terrain sis en territoire français et donne à bail au CERN - Projets lettre d'interprétation et accuse de réception
CERN/0529/Rev./Add.
28th Session of Council ; 1964
English: PDF
French: PDF
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