Zobrazeno 1 - 10
of 2 406
pro vyhledávání: '"A. Veneri"'
Autor:
Angeloni, Laura, Bloisi, Domenico Daniele, Burghignoli, Paolo, Comite, Davide, Costarelli, Danilo, Piconi, Michele, Sambucini, Anna Rita, Troiani, Alessio, Veneri, Alessandro
Human actions have accelerated changes in global temperature, precipitation patterns, and other critical Earth systems. Key markers of these changes can be linked to the dynamic of Essential Climate Variables (ECVs) and related quantities, such as So
Externí odkaz:
http://arxiv.org/abs/2412.03523
Autor:
Dosi, Andrea, Brescia, Massimo, Cavuoti, Stefano, D'Aniello, Mariarca, Veneri, Michele Delli, Donadio, Carlo, Ettari, Adriano, Longo, Giuseppe, Rownok, Alvi, Sannino, Luca, Zampella, Maria
Deep learning has revolutionized the field of hyperspectral image (HSI) analysis, enabling the extraction of complex and hierarchical features. While convolutional neural networks (CNNs) have been the backbone of HSI classification, their limitations
Externí odkaz:
http://arxiv.org/abs/2409.09386
Despite the recent success of identifying experimental signatures of the orbital Hall effect (OHE), the research on the microscopic mechanisms behind this unique phenomenon is still in its infancy. Here, using a gapped 2D Dirac material as a model sy
Externí odkaz:
http://arxiv.org/abs/2408.04492
This paper develops sharp testable implications for Tobit and IV-Tobit models' identifying assumptions: linear index specification, (joint) normality of latent errors, and treatment (instrument) exogeneity and relevance. The new sharp testable equali
Externí odkaz:
http://arxiv.org/abs/2408.02573
Publikováno v:
Physical Review B 109, L241404 (2024)
Atomically-thin materials based on transition metal dichalcogenides and graphene offer a promising avenue for unlocking the mechanisms underlying the spin Hall effect (SHE) in heterointerfaces. Here, we develop a microscopic theory of the SHE for twi
Externí odkaz:
http://arxiv.org/abs/2403.15229
Autor:
Gries, Thomas W., Regaldo, Davide, Koebler, Hans, Putri, Titan Noor Hartono, Sannino, Gennaro V., Partida, Emilio Gutierrez, Felix, Roberto, Huesam, Elif, Saleh, Ahmed, Wilks, Regan G., Iqbal, Zafar, Nia, Zahra Loghman, Ruske, Florian, Stolterfoht, Martin, Neher, Dieter, Baer, Marcus, Weber, Stefan A., Veneri, Paola Delli, Schulz, Philip, Puel, Jean-Baptiste, Kleider, Jean-Paul, Wang, Qiong, Unger, Eva, Musiienko, Artem, Abate, Antonio
Solar cells based on inorganic perovskite CsPbI3 are promising candidates to resolve the challenge of operational stability in the field of perovskite photovoltaics. For stable operation, however, it is crucial to thoroughly understand the extractive
Externí odkaz:
http://arxiv.org/abs/2403.11982
Autor:
Euclid Collaboration, Aussel, B., Kruk, S., Walmsley, M., Huertas-Company, M., Castellano, M., Conselice, C. J., Veneri, M. Delli, Sánchez, H. Domínguez, Duc, P. -A., Kuchner, U., La Marca, A., Margalef-Bentabol, B., Marleau, F. R., Stevens, G., Toba, Y., Tortora, C., Wang, L., Aghanim, N., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Cavuoti, S., Cimatti, A., Congedo, G., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Fotopoulou, S., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Tallada-Crespí, P., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Bolzonella, M., Boucaud, A., Bozzo, E., Burigana, C., Colodro-Conde, C., Di Ferdinando, D., Farinelli, R., Graciá-Carpio, J., Mainetti, G., Marcin, S., Mauri, N., Neissner, C., Nucita, A. A., Sakr, Z., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Baccigalupi, C., Ballardini, M., Borgani, S., Borlaff, A. S., Bretonnière, H., Bruton, S., Cabanac, R., Calabro, A., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Cañas-Herrera, G., Chambers, K. C., Coupon, J., Cucciati, O., Davini, S., De Lucia, G., Desprez, G., Di Domizio, S., Dole, H., Díaz-Sánchez, A., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., García-Bellido, J., Gaztanaga, E., George, K., Giacomini, F., Gozaliasl, G., Gregorio, A., Guinet, D., Hall, A., Hildebrandt, H., Munoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Maoli, R., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maturi, M., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Walton, Nicholas A., Peel, A., Pezzotta, A., Popa, V., Porciani, C., Potter, D., Pöntinen, M., Reimberg, P., Rocci, P. -F., Sánchez, A. G., Schneider, A., Sefusatti, E., Sereno, M., Simon, P., Mancini, A. Spurio, Stanford, S. A., Steinwagner, J., Testera, G., Tewes, M., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Zinchenko, I. A.
Publikováno v:
A&A 689, A274 (2024)
The Euclid mission is expected to image millions of galaxies with high resolution, providing an extensive dataset to study galaxy evolution. We investigate the application of deep learning to predict the detailed morphologies of galaxies in Euclid us
Externí odkaz:
http://arxiv.org/abs/2402.10187
Autor:
Valvano, Gabriele, Agostino, Antonino, De Magistris, Giovanni, Graziano, Antonino, Veneri, Giacomo
Publikováno v:
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024, pp. 5354-5363
Training supervised deep neural networks that perform defect detection and segmentation requires large-scale fully-annotated datasets, which can be hard or even impossible to obtain in industrial environments. Generative AI offers opportunities to en
Externí odkaz:
http://arxiv.org/abs/2401.03152
Autor:
Guglielmetti, Fabrizia, Veneri, Michele Delli, Baronchelli, Ivano, Blanco, Carmen, Dosi, Andrea, Enßlin, Torsten, Johnson, Vishal, Longo, Giuseppe, Roth, Jakob, Stoehr, Felix, Tychoniec, Łukasz, Villard, Eric
An ESO internal ALMA development study, BRAIN, is addressing the ill-posed inverse problem of synthesis image analysis employing astrostatistics and astroinformatics. These emerging fields of research offer interdisciplinary approaches at the interse
Externí odkaz:
http://arxiv.org/abs/2311.10657
The design process of centrifugal compressors requires applying an optimization process which is computationally expensive due to complex analytical equations underlying the compressor's dynamical equations. Although the regression surrogate models c
Externí odkaz:
http://arxiv.org/abs/2309.02818