Zobrazeno 1 - 10
of 2 379
pro vyhledávání: '"Giles C"'
Autor:
Tommaso Dorigo, Martina Fumanelli, Chiara Maccani, Marija Mojsovska, Giles C. Strong, Bruno Scarpa
Publikováno v:
Journal of High Energy Physics, Vol 2023, Iss 1, Pp 1-46 (2023)
Abstract The unsupervised search for overdense regions in high-dimensional feature spaces, where locally high population densities may be associated with anomalous contaminations to an otherwise more uniform population, is of relevance to application
Externí odkaz:
https://doaj.org/article/f3918e2ba85e4322a75b47574f12bf36
Autor:
Tommaso Dorigo, Andrea Giammanco, Pietro Vischia, Max Aehle, Mateusz Bawaj, Alexey Boldyrev, Pablo de Castro Manzano, Denis Derkach, Julien Donini, Auralee Edelen, Federica Fanzago, Nicolas R. Gauger, Christian Glaser, Atılım G. Baydin, Lukas Heinrich, Ralf Keidel, Jan Kieseler, Claudius Krause, Maxime Lagrange, Max Lamparth, Lukas Layer, Gernot Maier, Federico Nardi, Helge E.S. Pettersen, Alberto Ramos, Fedor Ratnikov, Dieter Röhrich, Roberto Ruiz de Austri, Pablo Martínez Ruiz del Árbol, Oleg Savchenko, Nathan Simpson, Giles C. Strong, Angela Taliercio, Mia Tosi, Andrey Ustyuzhanin, Haitham Zaraket
Publikováno v:
Reviews in Physics, Vol 10, Iss , Pp 100085- (2023)
The full optimization of the design and operation of instruments whose functioning relies on the interaction of radiation with matter is a super-human task, due to the large dimensionality of the space of possible choices for geometry, detection tech
Externí odkaz:
https://doaj.org/article/226f133fd21c4e9e8e0f30edd0daec70
Autor:
Giles C Strong, Maxime Lagrange, Aitor Orio, Anna Bordignon, Florian Bury, Tommaso Dorigo, Andrea Giammanco, Mariam Heikal, Jan Kieseler, Max Lamparth, Pablo Martínez Ruíz del Árbol, Federico Nardi, Pietro Vischia, Haitham Zaraket
Publikováno v:
Machine Learning: Science and Technology, Vol 5, Iss 3, p 035002 (2024)
We describe a software package, TomOpt, developed to optimise the geometrical layout and specifications of detectors designed for tomography by scattering of cosmic-ray muons. The software exploits differentiable programming for the modeling of muon
Externí odkaz:
https://doaj.org/article/b5fd5028d124413e83af68a527d8d56d
Publikováno v:
European Physical Journal C: Particles and Fields, Vol 82, Iss 1, Pp 1-26 (2022)
Abstract The performance demands of future particle-physics experiments investigating the high-energy frontier pose a number of new challenges, forcing us to find improved solutions for the detection, identification, and measurement of final-state pa
Externí odkaz:
https://doaj.org/article/6222f6046d574382bf28fc96ba8e7800
A novel pseudocode search engine is designed to facilitate efficient retrieval and search of academic papers containing pseudocode. By leveraging Elasticsearch, the system enables users to search across various facets of a paper, such as the title, a
Externí odkaz:
http://arxiv.org/abs/2411.12649
Resolving the dichotomy between the human-like yet constrained reasoning processes of Cognitive Architectures and the broad but often noisy inference behavior of Large Language Models (LLMs) remains a challenging but exciting pursuit, for enabling re
Externí odkaz:
http://arxiv.org/abs/2408.09176
Pseudocode in a scholarly paper provides a concise way to express the algorithms implemented therein. Pseudocode can also be thought of as an intermediary representation that helps bridge the gap between programming languages and natural languages. H
Externí odkaz:
http://arxiv.org/abs/2406.04635
Autor:
Anna Stakia, Tommaso Dorigo, Giovanni Banelli, Daniela Bortoletto, Alessandro Casa, Pablo de Castro, Christophe Delaere, Julien Donini, Livio Finos, Michele Gallinaro, Andrea Giammanco, Alexander Held, Fabricio Jiménez Morales, Grzegorz Kotkowski, Seng Pei Liew, Fabio Maltoni, Giovanna Menardi, Ioanna Papavergou, Alessia Saggio, Bruno Scarpa, Giles C. Strong, Cecilia Tosciri, João Varela, Pietro Vischia, Andreas Weiler
Publikováno v:
Reviews in Physics, Vol 7, Iss , Pp 100063- (2021)
Between the years 2015 and 2019, members of the Horizon 2020-funded Innovative Training Network named “AMVA4NewPhysics” studied the customization and application of advanced multivariate analysis methods and statistical learning tools to high-ene
Externí odkaz:
https://doaj.org/article/25b70fead16849348ede3777110406cd
Prompting techniques have significantly enhanced the capabilities of Large Language Models (LLMs) across various complex tasks, including reasoning, planning, and solving math word problems. However, most research has predominantly focused on languag
Externí odkaz:
http://arxiv.org/abs/2405.13209
Autor:
Hsu, Ting-Yao, Huang, Chieh-Yang, Huang, Shih-Hong, Rossi, Ryan, Kim, Sungchul, Yu, Tong, Giles, C. Lee, Huang, Ting-Hao K.
Crafting effective captions for figures is important. Readers heavily depend on these captions to grasp the figure's message. However, despite a well-developed set of AI technologies for figures and captions, these have rarely been tested for usefuln
Externí odkaz:
http://arxiv.org/abs/2403.17784