Complex Algorithms for Data-Driven Model Learning in Science and Engineering
Article dans une revue avec comité de lecture
Author
MONTÁNS, Francisco J.GÓMEZ-BOMBARELLI, RafaelKUTZ, J. Nathan 
CHINESTA SORIA, FranciscoAbstract
no abstract
Files in this item
Related items
Showing items related by title, author, creator and subject.
-
Article dans une revue avec comité de lecture; ; ;CHINESTA SORIA, Francisco (Wiley, 2019)
In their first centuries, scientific and engineering develop-ments were dominated by empirical understanding which encapsulated the first paradigm of scientific discovery. After the Renaissance, the scientific revolution ...
-
Article dans une revue avec comité de lecture;CHINESTA SORIA, Francisco; ; (Elsevier Masson, 2019)
In the past, data in which science and engineering is based, was scarce and frequently obtained by experiments proposed to verify a given hypothesis. Each experiment was able to yield only very limited data. Today, data ...
-
Article dans une revue avec comité de lecture; ; ;CHINESTA SORIA, Francisco (Frontiers Media SA, 2022-05)
We propose an efficient method to determine the micro-structural entropic behavior of polymer chains directly from a sufficiently rich non-homogeneous experiment at the continuum scale. The procedure is developed in 2 ...
-
Article dans une revue avec comité de lecture; ; ; ; ; ;CHINESTA SORIA, Francisco (Taylor & Francis, 2019)
The main objective of this study is to combine the statistical shape analysis with a morphing procedure in order to generate shape-parametric finite element models of tissues and organs and to explore the reliability and ...
-
Article dans une revue avec comité de lecture; ; ; ; ; ;CHINESTA SORIA, Francisco (Elsevier, 2019)
Background and objective: This paper focuses on computer simulation aspects of Digital Twin models in the medical framework. In particular, it addresses the need of fast and accurate simulators for the mechanical response ...