Zobrazeno 1 - 10
of 5 985
pro vyhledávání: '"Bernabè, A."'
Autor:
Szwarcman, Daniela, Roy, Sujit, Fraccaro, Paolo, Gíslason, Þorsteinn Elí, Blumenstiel, Benedikt, Ghosal, Rinki, de Oliveira, Pedro Henrique, Almeida, Joao Lucas de Sousa, Sedona, Rocco, Kang, Yanghui, Chakraborty, Srija, Wang, Sizhe, Kumar, Ankur, Truong, Myscon, Godwin, Denys, Lee, Hyunho, Hsu, Chia-Yu, Asanjan, Ata Akbari, Mujeci, Besart, Keenan, Trevor, Arevalo, Paulo, Li, Wenwen, Alemohammad, Hamed, Olofsson, Pontus, Hain, Christopher, Kennedy, Robert, Zadrozny, Bianca, Cavallaro, Gabriele, Watson, Campbell, Maskey, Manil, Ramachandran, Rahul, Moreno, Juan Bernabe
This technical report presents Prithvi-EO-2.0, a new geospatial foundation model that offers significant improvements over its predecessor, Prithvi-EO-1.0. Trained on 4.2M global time series samples from NASA's Harmonized Landsat and Sentinel-2 data
Externí odkaz:
http://arxiv.org/abs/2412.02732
Autor:
Ricardo, Barrios-Munoz, Matteo, Bernabe, David, Lopez-Perez, David, Gomez-Barquero, Israel, Quintanilla-Garcia
This paper examines the communication performance of unmanned aerial vehicles (UAVs) in dense urban environments, specifically in Benidorm, Spain. Through a comprehensive measurement campaign, we assessed key performance indicators (KPIs) relating to
Externí odkaz:
http://arxiv.org/abs/2411.09666
Autor:
Roy, Sujit, Singh, Talwinder, Freitag, Marcus, Schmude, Johannes, Lal, Rohit, Hegde, Dinesha, Ranjan, Soumya, Lin, Amy, Gaur, Vishal, Vos, Etienne Eben, Ghosal, Rinki, Patro, Badri Narayana, Aydin, Berkay, Pogorelov, Nikolai, Moreno, Juan Bernabe, Maskey, Manil, Ramachandran, Rahul
Deep learning-based methods have been widely researched in the areas of language and vision, demonstrating their capacity to understand long sequences of data and their usefulness in numerous helio-physics applications. Foundation models (FMs), which
Externí odkaz:
http://arxiv.org/abs/2410.10841
Autor:
Schmude, Johannes, Roy, Sujit, Trojak, Will, Jakubik, Johannes, Civitarese, Daniel Salles, Singh, Shraddha, Kuehnert, Julian, Ankur, Kumar, Gupta, Aman, Phillips, Christopher E, Kienzler, Romeo, Szwarcman, Daniela, Gaur, Vishal, Shinde, Rajat, Lal, Rohit, Da Silva, Arlindo, Diaz, Jorge Luis Guevara, Jones, Anne, Pfreundschuh, Simon, Lin, Amy, Sheshadri, Aditi, Nair, Udaysankar, Anantharaj, Valentine, Hamann, Hendrik, Watson, Campbell, Maskey, Manil, Lee, Tsengdar J, Moreno, Juan Bernabe, Ramachandran, Rahul
Triggered by the realization that AI emulators can rival the performance of traditional numerical weather prediction models running on HPC systems, there is now an increasing number of large AI models that address use cases such as forecasting, downs
Externí odkaz:
http://arxiv.org/abs/2409.13598
In this article, we introduce a method to optimize 5G massive multiple-input multiple-output (mMIMO) connectivity for unmanned aerial vehicles (UAVs) on aerial highways through strategic cell association. UAVs operating in 3D space encounter distinct
Externí odkaz:
http://arxiv.org/abs/2409.01812
Autor:
Hamann, Hendrik F., Brunschwiler, Thomas, Gjorgiev, Blazhe, Martins, Leonardo S. A., Puech, Alban, Varbella, Anna, Weiss, Jonas, Bernabe-Moreno, Juan, Massé, Alexandre Blondin, Choi, Seong, Foster, Ian, Hodge, Bri-Mathias, Jain, Rishabh, Kim, Kibaek, Mai, Vincent, Mirallès, François, De Montigny, Martin, Ramos-Leaños, Octavio, Suprême, Hussein, Xie, Le, Youssef, El-Nasser S., Zinflou, Arnaud, Belyi, Alexander J., Bessa, Ricardo J., Bhattarai, Bishnu Prasad, Schmude, Johannes, Sobolevsky, Stanislav
Foundation models (FMs) currently dominate news headlines. They employ advanced deep learning architectures to extract structural information autonomously from vast datasets through self-supervision. The resulting rich representations of complex syst
Externí odkaz:
http://arxiv.org/abs/2407.09434
Autor:
Mehonic, Adnan, Ielmini, Daniele, Roy, Kaushik, Mutlu, Onur, Kvatinsky, Shahar, Serrano-Gotarredona, Teresa, Linares-Barranco, Bernabe, Spiga, Sabina, Savelev, Sergey, Balanov, Alexander G, Chawla, Nitin, Desoli, Giuseppe, Malavena, Gerardo, Compagnoni, Christian Monzio, Wang, Zhongrui, Yang, J Joshua, Syed, Ghazi Sarwat, Sebastian, Abu, Mikolajick, Thomas, Noheda, Beatriz, Slesazeck, Stefan, Dieny, Bernard, Tuo-Hung, Hou, Varri, Akhil, Bruckerhoff-Pluckelmann, Frank, Pernice, Wolfram, Zhang, Xixiang, Pazos, Sebastian, Lanza, Mario, Wiefels, Stefan, Dittmann, Regina, Ng, Wing H, Buckwell, Mark, Cox, Horatio RJ, Mannion, Daniel J, Kenyon, Anthony J, Lu, Yingming, Yang, Yuchao, Querlioz, Damien, Hutin, Louis, Vianello, Elisa, Chowdhury, Sayeed Shafayet, Mannocci, Piergiulio, Cai, Yimao, Sun, Zhong, Pedretti, Giacomo, Strachan, John Paul, Strukov, Dmitri, Gallo, Manuel Le, Ambrogio, Stefano, Valov, Ilia, Waser, Rainer
The roadmap is organized into several thematic sections, outlining current computing challenges, discussing the neuromorphic computing approach, analyzing mature and currently utilized technologies, providing an overview of emerging technologies, add
Externí odkaz:
http://arxiv.org/abs/2407.02353
Autor:
González-Otero, Mauro, Cepa, Jordi, Padilla-Torres, Carmen P., Lara-López, Maritza A., González, J. Jesús, Bongiovanni, Ángel, Cedrés, Bernabé, Cerviño, Miguel, Cruz-González, Irene, Elías-Chávez, Mauricio, Herrera-Edoqui, Martín, Ibarra-Medel, Héctor J., Krongold, Yair, Nadolny, Jakub, Negrete, C. Alenka, García, Ana María Pérez, De Diego, José A., González-Serrano, J. Ignacio, Hernández-Toledo, Héctor, Pérez-Martínez, Ricardo, Sánchez-Portal, Miguel
Publikováno v:
A&A 687, A19 (2024)
Methods.We applied distinct selection criteria to attain an SFG sample with minimal AGN contamination. Multiple approaches were used to estimate the intrinsic extinction, SFR and gas-phase metallicity for the SFGs. In conjunction with findings in the
Externí odkaz:
http://arxiv.org/abs/2404.13629
Autor:
Patino-Saucedo, Alberto, Meijer, Roy, Yousefzadeh, Amirreza, Gomony, Manil-Dev, Corradi, Federico, Detteter, Paul, Garrido-Regife, Laura, Linares-Barranco, Bernabe, Sifalakis, Manolis
Configurable synaptic delays are a basic feature in many neuromorphic neural network hardware accelerators. However, they have been rarely used in model implementations, despite their promising impact on performance and efficiency in tasks that exhib
Externí odkaz:
http://arxiv.org/abs/2404.10597
Autor:
Fiorelli, Rafaella, Rajabali, Mona, Méndez-Romero, Roberto, Kumar, Akash, Litvinenko, Artem, Serrano-Gotarredona, Teresa, Moradi, Farshad, Åkerman, Johan, Linares-Barranco, Bernabé, Peralías, Eduardo
Publikováno v:
IEEE Transactions on Electron Devices 2024
As nascent nonlinear oscillators, nano-constriction spin Hall nano-oscillators (SHNOs) represent a promising potential for integration into more complicated systems such as neural networks, magnetic field sensors, and radio frequency (RF) signal clas
Externí odkaz:
http://arxiv.org/abs/2404.10334