A Robust Solution to Variational Importance Sampling of Minimum Variance

Autor: Jerónimo Hernández-González, Jesús Cerquides

Publikováno v: Entropy, Vol 22, Iss 12, p 1405 (2020)

Importance sampling is a Monte Carlo method where samples are obtained from an alternative proposal distribution. This can be used to focus the sampling process in the relevant parts of space, thus reducing the variance. Selecting the proposal that l

Externí odkaz: https://doaj.org/article/d927387fd7a741598e55776deb1ac869

Bayesian Optimization with Additive Kernels for a Stepwise Calibration of Simulation Models for Cost-Effectiveness Analysis

Autor: David Gómez-Guillén, Mireia Díaz, Josep Lluís Arcos, Jesus Cerquides

Publikováno v: International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-12 (2024)

Abstract A critical aspect of simulation models used in cost-effectiveness analysis lies in accurately representing the natural history of diseases, requiring parameters such as probabilities and disease burden rates. While most of these parameters c

Externí odkaz: https://doaj.org/article/b8a2f21d4bae4d1bba5082dba5dd3cc1

Limits of Conventional Machine Learning Methods to Predict Pregnancy and Multiple Pregnancy After Embryo Transfer

Autor: Núria Correa, Rita Vassena, Jesús Cerquides, Josep Lluís Arcos

When training models to learn the relationship between two or more variables, we expect to see previously demonstrated knowledge about that relationship reflected in the resulting estimators. For some domains, such as healthcare, it is imperative for

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5ebebd8229b4e639ce425d7861492c7e
https://doi.org/10.3233/faia210141

Solving highly cyclic distributed optimization problems without busting the bank: a decimation-based approach

Autor: Rémi Emonet, Juan A. Rodríguez-Aguilar, Gauthier Picard, Jesús Cerquides

Publikováno v: Logic Journal of the IGPL
Logic Journal of the IGPL, Oxford University Press (OUP), 2021, 29 (1), pp.72-95. ⟨10.1093/jigpal/jzaa069⟩
Digital.CSIC. Repositorio Institucional del CSIC
instname

[EN]In the context of solving large distributed constraint optimization problems, belief-propagation and incomplete inference algorithms are candidates of choice. However, in general, when the problem structure is very cyclic, these solution methods

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad1bd8b1e43befcf9d0777802c57bd03
https://hal.archives-ouvertes.fr/hal-02133894

Enriched Music-supported Therapy for chronic stroke patients : a study protocol of a randomised controlled trial

Autor: David Sanchez-Pinsach, Antoni Rodríguez-Fornells, Josep Lluis Arcos, Alan Turry, Esther Duarte, Emma Segura, Teppo Särkämö, Jesús Cerquides, Preeti Raghavan, Jennifer Grau-Sánchez, Anna Palumbo, Thomas F. Münte

Publikováno v: Dipòsit Digital de Documents de la UAB
Universitat Autònoma de Barcelona
Digital.CSIC. Repositorio Institucional del CSIC
instname
Dipòsit Digital de la UB
Universidad de Barcelona
BMC Neurology
BMC Neurology, Vol 21, Iss 1, Pp 1-16 (2021)

[EN]Abstract Background: Residual motor deficits of the upper limb in patients with chronic stroke are common and have a negative impact on autonomy, participation and quality of life. Music-Supported Therapy (MST) is an effective intervention to enh

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2667f1ca9a6f621af99559facfb5c23e
https://ddd.uab.cat/record/235647