標題: Titlebook: Domain Generalization with Machine Learning in the NOvA Experiment; Andrew T.C. Sutton Book 2023 The Editor(s) (if applicable) and The Aut [打印本頁] 作者: vitamin-D 時間: 2025-3-21 16:10
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書目名稱Domain Generalization with Machine Learning in the NOvA Experiment網絡公開度學科排名
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書目名稱Domain Generalization with Machine Learning in the NOvA Experiment年度引用學科排名
書目名稱Domain Generalization with Machine Learning in the NOvA Experiment讀者反饋
書目名稱Domain Generalization with Machine Learning in the NOvA Experiment讀者反饋學科排名
作者: 昏迷狀態(tài) 時間: 2025-3-21 20:51
A Review of Neutrino Physics,ystematically and unify them in a manner that obeys mathematical restrictions motivated by physical observations. From those theories we can model complex interactions and understand one of the most interesting puzzles that neutrinos have to offer: neutrino oscillations or the sponatneuous transitio作者: Inferior 時間: 2025-3-22 04:14 作者: 蒸發(fā) 時間: 2025-3-22 06:04 作者: concentrate 時間: 2025-3-22 12:23
The 3-Flavor Analysis,ned neutrino oscillation parameters: ., ., and .. A number of selection criteria are applied in order to isolate high-purity ., .), ., and .) samples in both the Near and Far detectors. We use the Near Detector to predict what we expect to see at the Far Detector under the various combinations of th作者: 等級的上升 時間: 2025-3-22 13:03
A Long Short-Term Memory Neural Network,accurate estimation of the energies of the outgoing particles from a neutrino interaction is crucial. In the standard NOvA analysis a simple energy estimator is used for the . interactions where the muon energy is determined by the length of its track and the energy of the hadronic system is estimat作者: 等級的上升 時間: 2025-3-22 20:47
Domain Generalization by Adversarial Training,y simulation is inherently an imperfect representation of the real physical processes that these networks are meant to target. In the jargon of machine learning, we are training networks on one domain and then applying them to another. When we do this, it can be beneficial to “generalize” or “adapt”作者: Mangle 時間: 2025-3-22 21:38 作者: 干旱 時間: 2025-3-23 01:25 作者: custody 時間: 2025-3-23 07:18 作者: 巫婆 時間: 2025-3-23 10:29
Andrew T.C. SuttonNominated as an outstanding thesis by the University of Virginia, USA.Reviews the history and physics of the neutrino.Shows how domain generalization can reduce the impact of uncertainties in HEP expe作者: Flustered 時間: 2025-3-23 15:17 作者: Contort 時間: 2025-3-23 20:10
A Review of Neutrino Physics,ystematically and unify them in a manner that obeys mathematical restrictions motivated by physical observations. From those theories we can model complex interactions and understand one of the most interesting puzzles that neutrinos have to offer: neutrino oscillations or the sponatneuous transition from one distinct particle to another.作者: extract 時間: 2025-3-23 22:29 作者: 以煙熏消毒 時間: 2025-3-24 02:41
Social Identity in a Divided Cyprusystematically and unify them in a manner that obeys mathematical restrictions motivated by physical observations. From those theories we can model complex interactions and understand one of the most interesting puzzles that neutrinos have to offer: neutrino oscillations or the sponatneuous transitio作者: 食草 時間: 2025-3-24 09:44
https://doi.org/10.1007/978-3-319-30552-3f 2 GeV and a separation of 809 km, NOvA is setup to observe the first oscillation maximum where the majority of muon-type neutrinos have turned into either electon or tau-type neutrinos. The NOvA experiment, being composed of materials with a low atomic number, was designed to efficiently detect bo作者: 特別容易碎 時間: 2025-3-24 14:24
Pam Denbesten,Robert Faller,Yukiko Nakanoed where nearby hits in time and space are grouped together as they are likely to have come from the same source. Next, we begin to resolve individual particles, and apply machine learning techniques to determine their specific types. Finally, in order to perform our physics analyses, we must estima作者: seduce 時間: 2025-3-24 18:45 作者: 疏遠天際 時間: 2025-3-24 20:33 作者: 斗志 時間: 2025-3-25 03:08
Pam Denbesten,Robert Faller,Yukiko Nakanoy simulation is inherently an imperfect representation of the real physical processes that these networks are meant to target. In the jargon of machine learning, we are training networks on one domain and then applying them to another. When we do this, it can be beneficial to “generalize” or “adapt”作者: Amplify 時間: 2025-3-25 06:00 作者: 現存 時間: 2025-3-25 09:02 作者: FUSC 時間: 2025-3-25 12:59 作者: Interdict 時間: 2025-3-25 19:26 作者: 種族被根除 時間: 2025-3-25 20:13
The Early Enamel Carious Lesion is a type of recurrent neural network that is well suited to the particle physics where the number of outgoing particles is not known a-priori and the energies of those particles are all physically linked to eachother.作者: 口訣法 時間: 2025-3-26 03:11
Pam Denbesten,Robert Faller,Yukiko NakanoTM network is also asked to identify which domain each event belongs to, and is penalized if it is able to do so correctly. This method pushes the LSTM away from features that distinguish between the domains and toward a middle ground that is more representative of reality.作者: 妨礙議事 時間: 2025-3-26 05:04
The 3-Flavor Analysis,en FD simulation and data is performed to find the minimum log-likelihood across the parameter space, and Feldman-Cousins (Phys Rev D 57:3873–3889, 1998) corrections are applied. With such a reliance on simulation and reconstruction techniques, we include many systematic uncertainties that are included in the fit as nuisance parameters.作者: ANTH 時間: 2025-3-26 09:00 作者: 顯微鏡 時間: 2025-3-26 14:19
Domain Generalization by Adversarial Training,TM network is also asked to identify which domain each event belongs to, and is penalized if it is able to do so correctly. This method pushes the LSTM away from features that distinguish between the domains and toward a middle ground that is more representative of reality.作者: altruism 時間: 2025-3-26 19:05 作者: 安定 時間: 2025-3-26 22:19
https://doi.org/10.1007/978-3-319-30552-3either electon or tau-type neutrinos. The NOvA experiment, being composed of materials with a low atomic number, was designed to efficiently detect both the muons and electrons that accompany a charge-current neutrino interaction.作者: pericardium 時間: 2025-3-27 03:34
Pam Denbesten,Robert Faller,Yukiko Nakano particles, and apply machine learning techniques to determine their specific types. Finally, in order to perform our physics analyses, we must estimate the energies associated with each particle and interaction.作者: anesthesia 時間: 2025-3-27 07:00 作者: outset 時間: 2025-3-27 13:07 作者: Foreshadow 時間: 2025-3-27 15:05
Event Reconstruction, particles, and apply machine learning techniques to determine their specific types. Finally, in order to perform our physics analyses, we must estimate the energies associated with each particle and interaction.作者: Cholesterol 時間: 2025-3-27 21:51 作者: cajole 時間: 2025-3-28 00:12 作者: 血統 時間: 2025-3-28 03:07 作者: 和諧 時間: 2025-3-28 07:09
Book 2023orks (NN) can be used to identify the particle types or determine their energies in detectors such as those used in the NOvA neutrino experiment, which studies changes in a beam of neutrinos as it propagates approximately 800 km through the earth. NOvA relies heavily on simulations of the physics pr作者: Blasphemy 時間: 2025-3-28 12:26
Domain Generalization with Machine Learning in the NOvA Experiment作者: 腫塊 時間: 2025-3-28 16:32
Book 2023tions will reduce the impact of uncertainties while avoiding the risk offalsely constraining the phase space. Reducing the impact of systematic uncertainties makes NOvA analysis more robust, and improves the significance of experimental results..作者: 戲法 時間: 2025-3-28 20:30
2190-5053 ng the phase space. Reducing the impact of systematic uncertainties makes NOvA analysis more robust, and improves the significance of experimental results..978-3-031-43585-0978-3-031-43583-6Series ISSN 2190-5053 Series E-ISSN 2190-5061
