Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Francesco Alesiani"'
Autor:
Viktor Zaverkin, David Holzmüller, Henrik Christiansen, Federico Errica, Francesco Alesiani, Makoto Takamoto, Mathias Niepert, Johannes Kästner
Publikováno v:
npj Computational Materials, Vol 10, Iss 1, Pp 1-18 (2024)
Abstract Efficiently creating a concise but comprehensive data set for training machine-learned interatomic potentials (MLIPs) is an under-explored problem. Active learning, which uses biased or unbiased molecular dynamics (MD) to generate candidate
Externí odkaz:
https://doaj.org/article/b80bd493f23e40339f5d153468a09724
Publikováno v:
Applied Artificial Intelligence, Vol 36, Iss 1 (2022)
eCommerce, postal and logistics’ planners require to solve large-scale capacitated vehicle routing problems (CVRPs) on a daily basis. CVRP problems are NP-Hard and cannot be easily solved for large problem instances. Given their complexity, we prop
Externí odkaz:
https://doaj.org/article/effb143683834485ba4a93c12d4037aa
Autor:
Sandra Mossuto, Enrico Attardi, Francesco Alesiani, Emanuele Angelucci, Enrico Balleari, Massimo Bernardi, Gianni Binotto, Costanza Bosi, Anna Calvisi, Isabella Capodanno, Antonella Carbone, Andrea Castelli, Marco Cerrano, Rosanna Ciancia, Daniela Cilloni, Marino Clavio, Cristina Clissa, Elena Crisà, Monica Crugnola, Matteo G. Della Porta, Nicola Di Renzo, Ambra Di Veroli, Roberto Fattizzo, Carmen Fava, Susanna Fenu, Ida L. Ferrara, Luana Fianchi, Carla Filì, Carlo Finelli, Valentina Giai, Francesco Frattini, Valentina Gaidano, Gianluca Guaragna, Svitlana Gumenyuk, Roberto Latagliata, Stefano Mancini, Emanuela Messa, Alfredo Molteni, Pellegrino Musto, Pasquale Niscola, Esther Oliva, Giuseppe A. Palumbo, Annamaria Pelizzari, Federica Pilo, Antonella Poloni, Marta Riva, Flavia Rivellini, Chiara Sarlo, Mariarita Sciumé, Roberto Secchi, Carmine Selleri, Agostino Tafuri, Valeria Santini
Publikováno v:
HemaSphere, Vol 4, Iss 5, p e483 (2020)
Externí odkaz:
https://doaj.org/article/213f028c785b49d69a37c0f28f6d7838
Autor:
Giuseppe Visani, Maria Rosaria Sapienza, Alessandro Isidori, Claudio Tripodo, Maria Antonella Laginestra, Simona Righi, Carlo A Sagramoso Sacchetti, Anna Gazzola, Claudia Mannu, Maura Rossi, Michele De Nictolis, Massimo Valentini, Meris Donati, Roberto Emiliani, Francesco Alesiani, Stefania Paolini, Carlo Finelli, Stefano A Pileri, Pier Paolo Piccaluga
Publikováno v:
PLoS ONE, Vol 6, Iss 11, p e27560 (2011)
The molecular pathogenesis of primary mielofibrosis (PMF) is still largely unknown. Recently, single-nucleotide polymorphism arrays (SNP-A) allowed for genome-wide profiling of copy-number alterations and acquired uniparental disomy (aUPD) at high-re
Externí odkaz:
https://doaj.org/article/c0c2faca824c478da37f38ee2dda2ef1
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031013324
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e06f85924a6ff85cdf6c419b3d62ab08
https://doi.org/10.1007/978-3-031-01333-1_23
https://doi.org/10.1007/978-3-031-01333-1_23
Publikováno v:
2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 1004-1010
STARTPAGE=1004;ENDPAGE=1010;TITLE=2021 IEEE International Intelligent Transportation Systems Conference (ITSC)
IEEE Xplore
ITSC
2021 IEEE International Intelligent Transportation Systems Conference (ITSC)
STARTPAGE=1004;ENDPAGE=1010;TITLE=2021 IEEE International Intelligent Transportation Systems Conference (ITSC)
IEEE Xplore
ITSC
2021 IEEE International Intelligent Transportation Systems Conference (ITSC)
This study introduces a model to solve a dynamic network optimization model on a heterogeneous graph. We use this model to optimize the collection and consolidation operations on a cross-country multi-modal distribution network. The model's dynamic o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::825069b397d474fab1d10cbe2b6f8cb2
https://doi.org/10.36227/techrxiv.16622896
https://doi.org/10.36227/techrxiv.16622896
Publikováno v:
Transportation research. Part E: Logistics and transportation review, 128, 30-51. Elsevier
Timetables are typically generated based on passenger demand and travel time expectations. This work incorporates the travel time and passenger demand uncertainty to generate robust timetables that minimize the possible loss at worst-case scenarios.
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 19:3698-3708
Today, we live in an era where pervasive sensor networks both collect and broadcast rich digital footprints about the human mobility. However, most of this data often comes in an incomplete and/or inaccurate fashion. In this paper, we propose a knowl
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030676605
ECML/PKDD (2)
ECML/PKDD (2)
Interpretable Multi-Task Learning can be expressed as learning a sparse graph of the task relationship based on the prediction performance of the learned models. Since many natural phenomenon exhibit sparse structures, enforcing sparsity on learned m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1dba4fbc181c5e2acd9acd5932591c54
https://doi.org/10.1007/978-3-030-67661-2_35
https://doi.org/10.1007/978-3-030-67661-2_35
Autor:
Gianni Cametti, Daniela Cilloni, Bernardino Allione, Paolo Danise, Emanuele Angelucci, Carmine Selleri, Flavia Salvi, Silvana Capalbo, Antonio Abbadessa, Manuela Ceccarelli, Monica Crugnola, Andrea Castelli, Massimo Catarini, Riccardo Centurioni, Fabio Guolo, Esther Oliva, Roberto Freilone, Catia Bigazzi, Pellegrino Musto, Marino Clavio, Renato Fanin, Maurizio Miglino, Dario Ferrero, Renato Zambello, Carlo Finelli, Francesco Alesiani, Antonella Poloni, Anna Angela Di Tucci, Valeria Santini, Elena Crisà, Enrico Balleari
BACKGROUND Azacitidine (AZA) is the standard treatment for myelodysplastic syndromes (MDS); however, many patients prematurely stop therapy and have a dismal outcome. METHODS The authors analyzed outcomes after AZA treatment for 402 MDS patients cons
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e2c8238c360ef117119fefb031b34bb
http://hdl.handle.net/2318/1784381
http://hdl.handle.net/2318/1784381