Zobrazeno 1 - 10
of 15 747
pro vyhledávání: '"Höll"'
Autor:
Griesemer, Tina, Ximenes, Rui Franqueira, Ahdida, Claudia, Izquierdo, Gonzalo Arnau, Santillana, Ignacio Aviles, Callaghan, Jack, Dumont, Gerald, Dutilleul, Thomas, Terricabras, Adria Gallifa, Höll, Stefan, Jacobsson, Richard, Kyffin, William, Mamun, Abdullah Al, Mazzola, Giuseppe, Fontenla, Ana Teresa Pérez, De Frutos, Oscar Sacristan, Esposito, Luigi Salvatore, Sgobba, Stefano, Calviani, Marco
Particle-producing targets in high-energy research facilities are often made from refractory metals, and they typically require dedicated cooling systems due to the challenging thermomechanical conditions they experience. However, direct contact of w
Externí odkaz:
http://arxiv.org/abs/2410.01988
Autor:
Griesemer, Tina, Ximenes, Rui Franqueira, Izquierdo, Gonzalo Arnau, Santillana, Ignacio Aviles, Brehm, Thomas, Terricabras, Adria Gallifa, Höll, Stefan, Jacobsson, Richard, Kaiser, Marco, Kuchar, Roman, Fontenla, Ana Teresa Pérez, Rempel, Alexey, De Frutos, Oscar Sacristan, Schienbein, Marcel, Sgobba, Stefano, Calviani, Marco
The Beam Dump Facility (BDF) is a planned fixed-target installation in CERN's North Area, set to start operating in 2031. A proton beam of 400 GeV/c will be delivered in 1 s pulses of 4e13 protons every 7.2 s, amounting to 4e19 protons on target (PoT
Externí odkaz:
http://arxiv.org/abs/2410.01964
As organizations face the challenges of processing exponentially growing data volumes, their reliance on analytics to unlock value from this data has intensified. However, the intricacies of big data, such as its extensive feature sets, pose signific
Externí odkaz:
http://arxiv.org/abs/2405.07658
Autor:
Toride, Kinya, Newman, Matthew, Hoell, Andrew, Capotondi, Antonietta, Schlör, Jakob, Amaya, Dillon J.
We introduce an interpretable-by-design method, optimized model-analog, that integrates deep learning with model-analog forecasting which generates forecasts from similar initial climate states in a repository of model simulations. This hybrid framew
Externí odkaz:
http://arxiv.org/abs/2404.15419
Autor:
Hoell, Nicholas
We present an expository overview of technical and cultural challenges to the development and adoption of automation at various stages in the data science prediction lifecycle, restricting focus to supervised learning with structured datasets. In add
Externí odkaz:
http://arxiv.org/abs/2208.11792