Zobrazeno 1 - 10
of 213
pro vyhledávání: '"Pablo, Moscato"'
Autor:
Pablo Moscato, Rafael Grebogi
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Understanding nuclear behaviour is fundamental in nuclear physics. This paper introduces a data-driven approach, Continued Fraction Regression (cf-r), to analyze nuclear binding energy (B(A, Z)). Using a tailored loss function and analytic c
Externí odkaz:
https://doaj.org/article/eb0e1647b7e2465198d8efafbaed0368
Autor:
Pablo Moscato, Mohammad Nazmul Haque
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract We present a new method for approximating two-body interatomic potentials from existing ab initio data based on representing the unknown function as an analytic continued fraction. In this study, our method was first inspired by a representa
Externí odkaz:
https://doaj.org/article/2a3b0ba8962a43a798a9cffb66ed209b
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-10 (2023)
Abstract We introduce new analytical approximations of the minimum electrostatic energy configuration of n electrons, E(n), when they are constrained to be on the surface of a unit sphere. Using 453 putative optimal configurations, we searched for ap
Externí odkaz:
https://doaj.org/article/2e1d55584ef3431a98075dd67eef47fd
Autor:
Pablo Moscato, Mohammad Nazmul Haque, Kevin Huang, Julia Sloan, Jonathon Corrales de Oliveira
Publikováno v:
Algorithms, Vol 16, Iss 8, p 382 (2023)
In the field of Artificial Intelligence (AI) and Machine Learning (ML), a common objective is the approximation of unknown target functions y=f(x) using limited instances S=(x(i),y(i)), where x(i)∈D and D represents the domain of interest. We refer
Externí odkaz:
https://doaj.org/article/4d006844b5ad48c98e594695c572c84d
Autor:
Benjamin Heng, Ayse A. Bilgin, David B. Lovejoy, Vanessa X. Tan, Heloisa H. Milioli, Laurence Gluch, Sonia Bustamante, Tharani Sabaretnam, Pablo Moscato, Chai K. Lim, Gilles J. Guillemin
Publikováno v:
Breast Cancer Research, Vol 22, Iss 1, Pp 1-14 (2020)
Abstract Background Immunotherapy has recently been proposed as a promising treatment to stop breast cancer (BrCa) progression and metastasis. However, there has been limited success in the treatment of BrCa with immune checkpoint inhibitors. This im
Externí odkaz:
https://doaj.org/article/2339ab5edf5e4945b152f4b86d3c26f6
Publikováno v:
BMC Medical Genomics, Vol 10, Iss 1, Pp 1-17 (2017)
Abstract Background Basal-like constitutes an important molecular subtype of breast cancer characterised by an aggressive behaviour and a limited therapy response. The outcome of patients within this subtype is, however, divergent. Some individuals s
Externí odkaz:
https://doaj.org/article/327465de276f4021acd77bbe88d3bd8a
Publikováno v:
Automated Software Engineering. 30
Autor:
Pablo Moscato, Mohammad Nazmul Haque
Modern methods for network analytics provide an opportunity to revisit preconceived notions in the classification of diseases as “clusters of symptoms”. Curated collections which were subsequently modified, like the Diagnostic and Statistical Man
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e9cc78d81890940ecf9c7fd989355c0
Publikováno v:
2022 IEEE Congress on Evolutionary Computation (CEC).
Publikováno v:
PLoS ONE, Vol 11, Iss 8, p e0157988 (2016)
In this study we propose a novel, unsupervised clustering methodology for analyzing large datasets. This new, efficient methodology converts the general clustering problem into the community detection problem in graph by using the Jensen-Shannon dist
Externí odkaz:
https://doaj.org/article/93ccb67495c34ae2992a6a77bb78d866