Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Òscar Garibo i Orts"'
Autor:
Gorka Muñoz-Gil, Giovanni Volpe, Miguel Angel Garcia-March, Erez Aghion, Aykut Argun, Chang Beom Hong, Tom Bland, Stefano Bo, J. Alberto Conejero, Nicolás Firbas, Òscar Garibo i Orts, Alessia Gentili, Zihan Huang, Jae-Hyung Jeon, Hélène Kabbech, Yeongjin Kim, Patrycja Kowalek, Diego Krapf, Hanna Loch-Olszewska, Michael A. Lomholt, Jean-Baptiste Masson, Philipp G. Meyer, Seongyu Park, Borja Requena, Ihor Smal, Taegeun Song, Janusz Szwabiński, Samudrajit Thapa, Hippolyte Verdier, Giorgio Volpe, Artur Widera, Maciej Lewenstein, Ralf Metzler, Carlo Manzo
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-16 (2021)
Deviations from Brownian motion leading to anomalous diffusion are ubiquitously found in transport dynamics but often difficult to characterize. Here the authors compare approaches for single trajectory analysis through an open competition, showing t
Externí odkaz:
https://doaj.org/article/5fe8e471b0bb497ab6891805cdc7e577
Autor:
Ahmed Begga, Òscar Garibo-i-Orts, Sergi de María-García, Francisco Escolano, Miguel A. Lozano, Nuria Oliver, J. Alberto Conejero
Publikováno v:
Frontiers in Public Health, Vol 11 (2023)
IntroductionDuring the recent COVID-19 pandemics, many models were developed to predict the number of new infections. After almost a year, models had also the challenge to include information about the waning effect of vaccines and by infection, and
Externí odkaz:
https://doaj.org/article/15767cbdd6664b37826413a51491216d
Publikováno v:
Mathematics, Vol 12, Iss 7, p 938 (2024)
The classification of time series using machine learning (ML) analysis and entropy-based features is an urgent task for the study of nonlinear signals in the fields of finance, biology and medicine, including EEG analysis and Brain–Computer Interfa
Externí odkaz:
https://doaj.org/article/3d456b71f8664930b4d771ddc7156e81
Autor:
Alejandro Sánchez-Roncero, Òscar Garibo-i-Orts, J. Alberto Conejero, Hamidreza Eivazi, Fermín Mallor, Emelie Rosenberg, Francesco Fuso-Nerini, Javier García-Martínez, Ricardo Vinuesa, Sergio Hoyas
Publikováno v:
Results in Engineering, Vol 17, Iss , Pp 100940- (2023)
The 2030 Agenda of the United Nations (UN) revolves around the Sustainable Development Goals (SDGs). A critical step towards that objective is identifying whether scientific production aligns with the SDGs' achievement. To assess this, funders and re
Externí odkaz:
https://doaj.org/article/474b5e26f1f44ea896c5c42870969afb
Publikováno v:
Physical Review E. 107
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe690276b8817c7a30962e3ade639961
https://doi.org/10.1103/physreve.107.034138
https://doi.org/10.1103/physreve.107.034138
Publikováno v:
Mathematical Methods in the Applied Sciences.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3bf1658163dee97d09cd6e60b68209b3
https://doi.org/10.1002/mma.9228
https://doi.org/10.1002/mma.9228
Autor:
Alejandro Sánchez-Roncero, Òscar Garibo-i-Orts, J. Alberto Conejero, Hamidreza Eivazi, Fermín Mallor, Emelie Rosenberg, Francesco Fuso-Nerini, Javier García-Martínez, Ricardo Vinuesa, Sergio Hoyas
The 2030 Agenda of the United Nations (UN) revolves around the Sustainable Development Goals (SDGs). A critical step towards that objective is identifying whether scientific production aligns with the SDGs' achievement. To assess this, funders and re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::83d9c404cba45e80f0e83be2e69be48d
http://arxiv.org/abs/2211.02409
http://arxiv.org/abs/2211.02409
We infer the parameters of fractional discrete Wu Baleanu time series by using machine learning architectures based on recurrent neural networks. Our results shed light on how clearly one can determine that a given trajectory comes from a specific fr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fcd5f3d84b8c91784439fb4d202badbc
https://doi.org/10.21203/rs.3.rs-2218679/v1
https://doi.org/10.21203/rs.3.rs-2218679/v1
Autor:
Miguel Angel Lozano, Òscar Garibo-i-Orts, Eloy Piñol, Miguel Rebollo, Kristina Polotskaya, Miguel Ángel García-March, J. Alberto Conejero, Francisco Escolano, Nuria Oliver
Publikováno v:
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence.
We describe the deep learning-based COVID-19 cases predictor and the Pareto-optimal Non-Pharmaceutical Intervention (NPI) prescriptor developed by the winning team of the 500k XPRIZE Pandemic Response Challenge. The competition aimed at developing da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d241a244589200b10465738df1c74872
https://doi.org/10.24963/ijcai.2022/740
https://doi.org/10.24963/ijcai.2022/740
Publikováno v:
Journal of Physics A: Mathematical and Theoretical. 56:014001
The results of the Anomalous Diffusion Challenge (AnDi Challenge) have shown that machine learning methods can outperform classical statistical methodology at the characterization of anomalous diffusion in both the inference of the anomalous diffusio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::96429e5ebd140f18b6eab74852d4b3b1
https://doi.org/10.1088/1751-8121/acafb3
https://doi.org/10.1088/1751-8121/acafb3