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A
C. Panigutti, Tizzoni, M., Bajardi, P., Smoreda, Z., and Colizza, V., “Assessing the use of mobile phone data to describe recurrent mobility patterns in spatial epidemic models”, Royal Society open science, vol. 4, p. 160950, 2017.
C
N. Atanov, Baranov, V., Budagov, J., Cervelli, F., Colao, F., Cordelli, M., Corradi, G., Dané, E., Davydov, Y. I., Di Falco, S., Diociaiuti, E., Donati, S., Donghia, R., Echenard, B., Flood, K., Giovannella, S., Glagolev, V., Grancagnolo, F., Happacher, F., Hitlin, D. G., Martini, M., Miscetti, S., Miyashita, T., Morescalchi, L., Murat, P., Pezzullo, G., Porter, F., Raffaelli, F., Radicioni, T., Ricci, M., Saputi, A., Sarra, I., Spinella, F., Tassielli, G., Tereshchenko, V., Usubov, Z., and Zhu, R. Y., “The calorimeter of the Mu2e experiment at Fermilab”, Journal of Instrumentation, vol. 12, 2017.
N. Atanov, Baranov, V., Budagov, J., Cervelli, F., Colao, F., Cordelli, M., Corradi, G., Dané, E., Davydov, Y. I., Di Falco, S., Diociaiuti, E., Donati, S., Donghia, R., Echenard, B., Flood, K., Giovannella, S., Glagolev, V., Grancagnolo, F., Happacher, F., Hitlin, D. G., Martini, M., Miscetti, S., Miyashita, T., Morescalchi, L., Murat, P., Pezzullo, G., Porter, F., Raffaelli, F., Radicioni, T., Ricci, M., Saputi, A., Sarra, I., Spinella, F., Tassielli, G., Tereshchenko, V., Usubov, Z., and Zhu, R. Y., “The calorimeter of the Mu2e experiment at Fermilab”, Journal of Instrumentation, vol. 12, 2017.
D
C. Panigutti, Perotti, A., and Pedreschi, D., “Doctor XAI: an ontology-based approach to black-box sequential data classification explanations”, in Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 2020.
C. Panigutti, Perotti, A., and Pedreschi, D., “Doctor XAI: an ontology-based approach to black-box sequential data classification explanations”, in Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 2020.
C. Panigutti, Perotti, A., and Pedreschi, D., “Doctor XAI: an ontology-based approach to black-box sequential data classification explanations”, in Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 2020.
V. Dib, Nalon, M. Aurélio, Amazonas, N. Tavares, Vidal, C. Yuri, Ortiz-Rodríguez, I. A., Daněk, J., de Oliveira, M. Formis, Alberti, P., da Silva, R. Aparecida, Precinoto, R. Salomão, and Gomes, T. Figueiredo, “Drivers of change in biodiversity and ecosystem services in the Cantareira System Protected Area : A prospective analysis of the implementation of public policies”, Biota Neotropica, vol. 20, no. 1, 2020.
M. Andreani and Petrella, L., “Dynamic Quantile Regression Forest”, SIS 2020 - 50th Conference of the Italian Statistical Society, vol. Book of Short Papers SIS 2020. Pearson, 2020.
E
S. Corbara, Moreo, A., Sebastiani, F., and Tavoni, M., “The Epistle to Cangrande Through the Lens of Computational Authorship Verification”, in New Trends in Image Analysis and Processing – ICIAP 2019, Cham, 2019.
C. Panigutti, Guidotti, R., Monreale, A., and Pedreschi, D., “Explaining multi-label black-box classifiers for health applications”, in International Workshop on Health Intelligence, 2019.
C. Panigutti, Guidotti, R., Monreale, A., and Pedreschi, D., “Explaining multi-label black-box classifiers for health applications”, in International Workshop on Health Intelligence, 2019.
M
M. Baltakiene, Baltakys, K., Cardamone, D., Parisi, F., Radicioni, T., Torricelli, M., de Jeude, J. A., and Saracco, F., “Maximum entropy approach to link prediction in bipartite networks”, arXiv preprint arXiv:1805.04307, 2018.
V. Voukelatou, Gabrielli, L., Miliou, I., Cresci, S., Sharma, R., Tesconi, M., and Pappalardo, L., “Measuring objective and subjective well-being: dimensions and data sources”, International Journal of Data Science and Analytics (JDSA), 2020.
M. Andreani, Candila, V., Morelli, G., and Petrella, L., “Multivariate Analysis of Energy Commodities during the COVID-19 Pandemic: Evidence from a Mixed-Frequency Approach”, Risks, vol. 9, p. 144, 2021.
N
D. Di Gangi, Sardo, D. R. Lo, Macchiati, V., Minh, T. P., Pinotti, F., Ramadiah, A., Wilinski, M., Barucca, P., and Cimini, G., “Network Sensitivity of Systemic Risk”, Journal of Network Theory in Finance, 2019.
Q
M. Andreani, Candila, V., and Petrella, L., “Quantile Regression Forest for Value-at-Risk Forecasting Via Mixed-Frequency Data”, Mathematical and Statistical Methods for Actuarial Sciences and Finance. Springer, Cham, 2022.
M. Andreani, Candila, V., and Petrella, L., “Quantile Regression Forest with mixed-frequency data”, vol. Book of Short Papers SIS 2021. Pearson, 2021.
S
V. Macchiati, Brandi, G., Di Matteo, T., Paolotti, D., Caldarelli, G., and Cimini, G., “Systemic liquidity contagion in the European interbank market”, Journal of Economic Interaction and Coordination, 2021.
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