Zobrazeno 1 - 10
of 8 065
pro vyhledávání: '"Kunkel P"'
Autor:
Giesselmann, Jan, Kunkel, Teresa
We study a state estimation problem for a $2\times 2$ linear hyperbolic system on networks with eigenvalues with opposite signs. The system can be seen as a simplified model for gas flow through gas networks. For this system we construct an observer
Externí odkaz:
http://arxiv.org/abs/2409.20345
Autor:
Bumberger, J., Abbrent, M., Brinckmann, N., Hemmen, J., Kunkel, R., Lorenz, C., Lünenschloß, P., Palm, B., Schnicke, T., Schulz, C., van der Schaaf, H., Schäfer, D.
Addressing the challenges posed by climate change, biodiversity loss, and environmental pollution requires comprehensive monitoring and effective data management strategies that are applicable across various scales in environmental system science. Th
Externí odkaz:
http://arxiv.org/abs/2409.03351
The widespread adoption of large language models (LLMs) has created a pressing need for an efficient, secure and private serving infrastructure, which allows researchers to run open source or custom fine-tuned LLMs and ensures users that their data r
Externí odkaz:
http://arxiv.org/abs/2407.00110
Publikováno v:
In Proceedings of the IARIA CloudComputing 2024 Conference (pp. 1-9). Venice, Italy. ISSN: 2308-4294. ISBN: 978-1-68558-156-5
The landscape of maintenance in distributed systems is rapidly evolving with the integration of Artificial Intelligence (AI). Also, as the complexity of computing continuum systems intensifies, the role of AI in predictive maintenance (Pd.M.) becomes
Externí odkaz:
http://arxiv.org/abs/2404.13454
Publikováno v:
JHEP 06 (2024) 092
Strong dynamics for composite Higgs models predict spin-1 resonances which are expected to be in the same mass range as the usually considered top-partners. We study here QCD-coloured vector and axial-vector states stemming from composite Higgs dynam
Externí odkaz:
http://arxiv.org/abs/2404.02198
Autor:
Kunkel, Lea, Trabs, Mathias
The empirical success of Generative Adversarial Networks (GANs) caused an increasing interest in theoretical research. The statistical literature is mainly focused on Wasserstein GANs and generalizations thereof, which especially allow for good dimen
Externí odkaz:
http://arxiv.org/abs/2403.15312
Autor:
MAGIC Collaboration, Abe, H., Abe, S., Abhir, J., Acciari, V. A., Agudo, I., Aniello, T., Ansoldi, S., Antonelli, L. A., Engels, A. Arbet, Arcaro, C., Artero, M., Asano, K., Baack, D., Babić, A., Baquero, A., de Almeida, U. Barres, Batković, I., Baxter, J., González, J. Becerra, Bernardini, E., Bernete, J., Berti, A., Besenrieder, J., Bigongiari, C., Biland, A., Blanch, O., Bonnoli, G., Bošnjak, Ž., Burelli, I., Busetto, G., Campoy-Ordaz, A., Carosi, A., Carosi, R., Carretero-Castrillo, M., Castro-Tirado, A. J., Chai, Y., Cifuentes, A., Cikota, S., Colombo, E., Contreras, J. L., Cortina, J., Covino, S., D'Amico, G., D'Elia, V., Da Vela, P., Dazzi, F., De Angelis, A., De Lotto, B., Del Popolo, A., Delfino, M., Delgado, J., Mendez, C. Delgado, Depaoli, D., Di Pierro, F., Di Venere, L., Prester, D. Dominis, Donini, A., Dorner, D., Doro, M., Elsaesser, D., Emery, G., Escudero, J., Fariña, L., Fattorini, A., Foffano, L., Font, L., Fukami, S., Fukazawa, Y., López, R. J. García, Gasparyan, S., Gaug, M., Paiva, J. G. Giesbrecht, Giglietto, N., Giordano, F., Gliwny, P., Grau, R., Green, J. G., Hadasch, D., Hahn, A., Heckmann, L., Herrera, J., Hovatta, T., Hrupec, D., Hütten, M., Imazawa, R., Inada, T., Iotov, R., Ishio, K., Martínez, I. Jiménez, Jormanainen, J., Kerszberg, D., Kluge, G. W., Kobayashi, Y., Kouch, P. M., Kubo, H., Kushida, J., Lezáun, M. Láinez, Lamastra, A., Leone, F., Lindfors, E., Liodakis, I., Lombardi, S., Longo, F., López-Moya, M., López-Oramas, A., Loporchio, S., Lorini, A., Fraga, B. Machado de Oliveira, Majumdar, P., Makariev, M., Maneva, G., Mang, N., Manganaro, M., Mannheim, K., Mariotti, M., Martínez, M., Martínez-Chicharro, M., Mas-Aguilar, A., Mazin, D., Menchiari, S., Mender, S., Miceli, D., Miener, T., Miranda, J. M., Mirzoyan, R., González, M. Molero, Molina, E., Mondal, H. A., Moralejo, A., Morcuende, D., Nakamori, T., Nanci, C., Neustroev, V., Nigro, C., Nikolić, L., Nilsson, K., Nishijima, K., Ekoume, T. Njoh, Noda, K., Nozaki, S., Ohtani, Y., Okumura, A., Otero-Santos, J., Paiano, S., Palatiello, M., Paneque, D., Paoletti, R., Paredes, J. M., Pavlović, D., Persic, M., Pihet, M., Pirola, G., Podobnik, F., Moroni, P. G. Prada, Prandini, E., Principe, G., Priyadarshi, C., Rhode, W., Ribó, M., Rico, J., Righi, C., Sahakyan, N., Saito, T., Satalecka, K., Saturni, F. G., Schleicher, B., Schmidt, K., Schmuckermaier, F., Schubert, J. L., Schweizer, T., Sciaccaluga, A., Sitarek, J., Spolon, A., Stamerra, A., Strišković, J., Strom, D., Suda, Y., Suutarinen, S., Tajima, H., Takeishi, R., Tavecchio, F., Temnikov, P., Terauchi, K., Terzić, T., Teshima, M., Tosti, L., Truzzi, S., Tutone, A., Ubach, S., van Scherpenberg, J., Ventura, S., Verguilov, V., Viale, I., Vigorito, C. F., Vitale, V., Walter, R., Wunderlich, C., Yamamoto, T., collaborators, MWL, Jermak, H., Steele, I. A., Smith, P. S., Blinov, D., Raiteri, C. M., Villata, M., Mirzaqulov, D. O., Kurtanidze, S. O., Carosati, D., Savchenko, S. S., Acosta-Pulido, J. A., Borman, G. A., Bozhilov, V., Carnerero, M. I., Chigladze, R. A., Damljanovic, G., Ehgamberdiev, S. A., Feige, M., Grishina, T. S., Gupta, A. C., Hagen-Thorn, V. A., Ibryamov, S., Ivanidze, R. Z., Jorstad, S. G., Kania, J., Kimeridze, G. N., Kopatskaya, E. N., Kopp, M., Kunkel, L., Kurtanidze, O. M., Larionov, V. M., Larionova, E. G., Larionova, L. V., Lorey, C., Marchini, A., Marscher, A. P., Minev, M., Morozova, D. A., Nikolashvili, M. G., Ovcharov, E., Reinhart, D., Sadun, A. C., Scherbantin, A., Schneider, L., Semkov, E., Sigua, L. A., Steineke, R., Troitskaya, Yu. V., Troitskiy, I. S., Valcheva, A., Vasilyev, A. A., Vince, O., Zaharieva, E., Zottmann, N., Kiehlmann, S., Readhead, A., Max-Moerbeck, W., Reeves, R. A., Sandrinelli, A., Ramazani, V. Fallah, Giroletti, M., Righini, S., Marchili, N., Patricelli, B., Ghirlanda, G., Lico, R.
PG 1553+113 is one of the few blazars with a convincing quasi-periodic emission in the gamma-ray band. The source is also a very high-energy (VHE; >100 GeV) gamma-ray emitter. To better understand its properties and identify the underlying physical p
Externí odkaz:
http://arxiv.org/abs/2403.02159
Autor:
Reuther, Albert, Brown, Nick, Arndt, William, Blaschke, Johannes, Boehme, Christian, Chazapis, Antony, Enders, Bjoern, Henschel, Robert, Kunkel, Julian, Martinasso, Maxime
As a broader set of applications from simulations to data analysis and machine learning require more parallel computational capability, the demand for interactive and urgent high performance computing (HPC) continues to increase. This paper overviews
Externí odkaz:
http://arxiv.org/abs/2401.14550
Autor:
da Costa, Cristiano André, Santos, Uélison Jean Lopes dos, Reis, Eduardo Souza dos, Antunes, Rodolfo Stoffel, Pacheco, Henrique Chaves, França, Thaynã da Silva, Righi, Rodrigo da Rosa, Barbosa, Jorge Luis Victória, Jebadoss, Franklin, Montalvao, Jorge, Kunkel, Rogerio
In this article, we provide an overview of the latest intelligent techniques used for processing business rules. We have conducted a comprehensive survey of the relevant literature on robot process automation, with a specific focus on machine learnin
Externí odkaz:
http://arxiv.org/abs/2311.11775
Autor:
Engels, R., El-Kordy, T., Faatz, N., Hanhart, C., Hanold, N., Kannis, C. S., Kunkel, L., Pütz, S., Sharma, H., Sefzick, T., Soltner, H., Verhoeven, V., Westphal, M., Wirtz, J., Büscher, M.
Sizable hyperpolarisation, i.e. an imbalance of the occupation numbers of nuclear spins in a sample deviating from thermal equilibrium, is needed in various fields of science. For example, hyperpolarised tracers are utilised in magnetic resonance ima
Externí odkaz:
http://arxiv.org/abs/2311.05976