Zobrazeno 1 - 10
of 2 451
pro vyhledávání: '"Á. de Frutos"'
Traditional implicit generative models are capable of learning highly complex data distributions. However, their training involves distinguishing real data from synthetically generated data using adversarial discriminators, which can lead to unstable
Externí odkaz:
http://arxiv.org/abs/2410.22381
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
Autor:
Huergo, David, de Frutos, Martín, Jané, Eduardo, Marino, Oscar A., Rubio, Gonzalo, Ferrer, Esteban
We present a novel approach to automate and optimize anisotropic p-adaptation in high-order h/p solvers using Reinforcement Learning (RL). The dynamic RL adaptation uses the evolving solution to adjust the high-order polynomials. We develop an offlin
Externí odkaz:
http://arxiv.org/abs/2407.19000
We develop a torque-pitch control framework using deep reinforcement learning for wind turbines to optimize the generation of wind turbine energy while minimizing operational noise. We employ a double deep Q-learning, coupled to a blade element momen
Externí odkaz:
http://arxiv.org/abs/2407.13320
Publikováno v:
Cuadernos de Investigación Geográfica, Vol 45, Iss 2, Pp 441-468 (2019)
Anthropogenic activities have modified vegetation on subalpine belts for a long time, lowering the treeline ecotone and influencing the landscape mainly through grazing and fire. The abandonment of these traditional land use practices during the last
Externí odkaz:
https://doaj.org/article/fed5227e1783407bb4908377537206e2
Autor:
J. C. Antuña-Marrero, V. Cachorro Revilla, F. García Parrado, Á. de Frutos Baraja, A. Rodríguez Vega, D. Mateos, R. Estevan Arredondo, C. Toledano
Publikováno v:
Atmospheric Measurement Techniques, Vol 11, Pp 2279-2293 (2018)
In the present study, we report the first comparison between the aerosol optical depth (AOD) and Ångström exponent (AE) of the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra (AODt) and Aqua (AODa) satellites and t
Externí odkaz:
https://doaj.org/article/44cc0921ed0648719551a0ace649e397
Implicit generative models have the capability to learn arbitrary complex data distributions. On the downside, training requires telling apart real data from artificially-generated ones using adversarial discriminators, leading to unstable training a
Externí odkaz:
http://arxiv.org/abs/2402.16435
We propose a reinforcement learning strategy to control wind turbine energy generation by actively changing the rotor speed, the rotor yaw angle and the blade pitch angle. A double deep Q-learning with a prioritized experience replay agent is coupled
Externí odkaz:
http://arxiv.org/abs/2402.11384
Autor:
Aceto, Luca, Fábregas, Ignacio, Escrig, David de Frutos, Ingólfsdóttir, Anna, Palomino, Miguel
Publikováno v:
Science of Computer Programming 78. 2013
This paper studies the relationships between three notions of behavioural preorder that have been proposed in the literature: refinement over modal transition systems, and the covariant-contravariant simulation and the partial bisimulation preorders
Externí odkaz:
http://arxiv.org/abs/2402.00966