Zobrazeno 1 - 10
of 1 366
pro vyhledávání: '"Posocco, P"'
Autor:
Lemaire, Valentin, Achenchabe, Youssef, Ody, Lucas, Souid, Houssem Eddine, Aversano, Gianmarco, Posocco, Nicolas, Skhiri, Sabri
The topic of synthetic graph generators (SGGs) has recently received much attention due to the wave of the latest breakthroughs in generative modelling. However, many state-of-the-art SGGs do not scale well with the graph size. Indeed, in the generat
Externí odkaz:
http://arxiv.org/abs/2309.15648
Autor:
G. Dreossi, M. Masiol, B. Stenni, D. Zannoni, C. Scarchilli, V. Ciardini, M. Casado, A. Landais, M. Werner, A. Cauquoin, G. Casasanta, M. Del Guasta, V. Posocco, C. Barbante
Publikováno v:
The Cryosphere, Vol 18, Pp 3911-3931 (2024)
A 10-year record of oxygen and hydrogen isotopic composition of precipitation is presented here: from 2008 to 2017, 1483 daily precipitation samples were collected year-round on a raised platform at Concordia Station, East Antarctica. Weather data we
Externí odkaz:
https://doaj.org/article/2bef00c59e0746aab3edeaaa9fffcd0d
In this paper, we study the behaviour of the triplet loss and show that it can be exploited to limit the biases created and perpetuated by machine learning models. Our fair classifier uses the collapse of the triplet loss when its margin is greater t
Externí odkaz:
http://arxiv.org/abs/2306.04400
Autor:
BABAR Collaboration, Lees, J. P., Poireau, V., Tisserand, V., Grauges, E., Palano, A., Eigen, G., Brown, D. N., Kolomensky, Yu. G., Fritsch, M., Koch, H., Cheaib, R., Hearty, C., Mattison, T. S., McKenna, J. A., So, R. Y., Blinov, V. E., Buzykaev, A. R., Druzhinin, V. P., Golubev, V. B., Kozyrev, E. A., Kravchenko, E. A., Onuchin, A. P., Serednyakov, S. I., Skovpen, Yu. I., Solodov, E. P., Todyshev, K. Yu., Lankford, A. J., Dey, B., Gary, J. W., Long, O., Eisner, A. M., Lockman, W. S., Vazquez, W. Panduro, Chao, D. S., Cheng, C. H., Echenard, B., Flood, K. T., Hitlin, D. G., Kim, J., Li, Y., Lin, D. X., Middleton, S., Miyashita, T. S., Ongmongkolkul, P., Oyang, J., Porter, F. C., Röhrken, M., Huard, Z., Meadows, B. T., Pushpawela, B. G., Sokoloff, M. D., Sun, L., Smith, J. G., Wagner, S. R., Bernard, D., Verderi, M., Bettoni, D., Bozzi, C., Calabrese, R., Cibinetto, G., Fioravanti, E., Garzia, I., Luppi, E., Santoro, V., Calcaterra, A., de Sangro, R., Finocchiaro, G., Martellotti, S., Patteri, P., Peruzzi, I. M., Piccolo, M., Rotondo, M., Zallo, A., Passaggio, S., Patrignani, C., Shuve, B. J., Lacker, H. M., Bhuyan, B., Mallik, U., Chen, C., Cochran, J., Prell, S., Gritsan, A. V., Arnaud, N., Davier, M., Diberder, F. Le, Lutz, A. M., Wormser, G., Lange, D. J., Wright, D. M., Coleman, J. P., Gabathuler, E., Hutchcroft, D. E., Payne, D. J., Touramanis, C., Bevan, A. J., Di Lodovico, F., Sacco, R., Cowan, G., Banerjee, Sw., Davis, C. L., Denig, A. G., Gradl, W., Griessinger, K., Hafner, A., Schubert, K. R., Barlow, R. J., Lafferty, G. D., Cenci, R., Jawahery, A., Roberts, D. A., Cowan, R., Robertson, S. H., Seddon, R. M., Neri, N., Palombo, F., Cremaldi, L., Godang, R., Summers, D. J., Taras, P., De Nardo, G., Sciacca, C., Raven, G., Jessop, C. P., LoSecco, J. M., Honscheid, K., Kass, R., Gaz, A., Margoni, M., Posocco, M., Simi, G., Simonetto, F., Stroili, R., Akar, S., Ben-Haim, E., Bomben, M., Bonneaud, G. R., Calderini, G., Chauveau, J., Marchiori, G., Ocariz, J., Biasini, M., Manoni, E., Rossi, A., Batignani, G., Bettarini, S., Carpinelli, M., Casarosa, G., Chrzaszcz, M., Forti, F., Giorgi, M. A., Lusiani, A., Oberhof, B., Paoloni, E., Rama, M., Rizzo, G., Walsh, J. J., Zani, L., Smith, A. J. S., Anulli, F., Faccini, R., Ferrarotto, F., Ferroni, F., Pilloni, A., Piredda, G., Bünger, C., Dittrich, S., Grünberg, O., Heß, M., Leddig, T., Voß, C., Waldi, R., Adye, T., Wilson, F. F., Emery, S., Vasseur, G., Aston, D., Cartaro, C., Convery, M. R., Dorfan, J., Dunwoodie, W., Ebert, M., Field, R. C., Fulsom, B. G., Graham, M. T., Hast, C., Innes, W. R., Kim, P., Leith, D. W. G. S., Luitz, S., MacFarlane, D. B., Muller, D. R., Neal, H., Ratcliff, B. N., Roodman, A., Sullivan, M. K., Va'vra, J., Wisniewski, W. J., Purohit, M. V., Wilson, J. R., Randle-Conde, A., Sekula, S. J., Ahmed, H., Tasneem, N., Bellis, M., Burchat, P. R., Puccio, E. M. T., Alam, M. S., Ernst, J. A., Gorodeisky, R., Guttman, N., Peimer, D. R., Soffer, A., Spanier, S. M., Ritchie, J. L., Schwitters, R. F., Izen, J. M., Lou, X. C., Bianchi, F., De Mori, F., Filippi, A., Gamba, D., Lanceri, L., Vitale, L., Martinez-Vidal, F., Oyanguren, A., Albert, J., Beaulieu, A., Bernlochner, F. U., King, G. J., Kowalewski, R., Lueck, T., Miller, C., Nugent, I. M., Roney, J. M., Sobie, R. J., Gershon, T. J., Harrison, P. F., Latham, T. E., Prepost, R., Wu, S. L.
Publikováno v:
PHYS. REV. D 107, 092001 (2023)
A new mechanism has been proposed to simultaneously explain the presence of dark matter and the matter-antimatter asymmetry in the universe. This scenario predicts exotic $B$ meson decays into a baryon and a dark sector anti-baryon ($\psi_D$) with br
Externí odkaz:
http://arxiv.org/abs/2302.00208
Autor:
Sara Gagno, Bianca Posocco, Marco Orleni, Eleonora Cecchin, Arianna Fumagalli, Michela Guardascione, Angela Buonadonna, Jerry Polesel, Fabio Puglisi, Giuseppe Toffoli, Erika Cecchin
Publikováno v:
Frontiers in Immunology, Vol 15 (2024)
IntroductionInflammatory factors released during severe coronavirus disease-19 (COVID-19) caused by acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are known to influence drug exposure, but data on the effect of mild infection are few. Here we
Externí odkaz:
https://doaj.org/article/b826ea85157a4f4c887a62980838c9f0
Autor:
Elena Peruzzi, Bianca Posocco, Lorenzo Gerratana, Margherita Nuti, Marco Orleni, Sara Gagno, Elena De Mattia, Fabio Puglisi, Erika Cecchin, Giuseppe Toffoli, Rossana Roncato
Publikováno v:
Frontiers in Pharmacology, Vol 15 (2024)
Palbociclib, an oral inhibitor of cyclin-dependent kinase 4 and 6, is approved for the treatment of metastatic breast cancer. This study investigated the influence of diverse clinical and biological factors—age, renal function, genetic variations,
Externí odkaz:
https://doaj.org/article/b521bc612660403e8b9680b8ad7af635
Trustworthy machine learning is driving a large number of ML community works in order to improve ML acceptance and adoption. The main aspect of trustworthy machine learning are the followings: fairness, uncertainty, robustness, explainability and for
Externí odkaz:
http://arxiv.org/abs/2207.03324
Autor:
Posocco, Nicolas, Bonnefoy, Antoine
Uncertainty in probabilistic classifiers predictions is a key concern when models are used to support human decision making, in broader probabilistic pipelines or when sensitive automatic decisions have to be taken. Studies have shown that most model
Externí odkaz:
http://arxiv.org/abs/2109.03480
Missing data is a recurrent and challenging problem, especially when using machine learning algorithms for real-world applications. For this reason, missing data imputation has become an active research area, in which recent deep learning approaches
Externí odkaz:
http://arxiv.org/abs/2106.16057
Anomaly detection is a widely explored domain in machine learning. Many models are proposed in the literature, and compared through different metrics measured on various datasets. The most popular metrics used to compare performances are F1-score, AU
Externí odkaz:
http://arxiv.org/abs/2106.16020