Documentos de Fernández J. | REDI

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Filtros aplicados

Publisher: "Engineering Applications of Artificial Intelligence"

Subtipo de publicación

Área temáticas

Ciencias de la computación(1)

Ingeniería y operaciones afines(1)

Área de conocimiento

Ciencia de materiales(1)

Material compuesto(1)

Red neuronal artificial(1)

Objetivos de Desarrollo Sostenible

ODS 9: Industria, innovación e infraestructura(2)

ODS 11: Ciudades y comunidades sostenibles(1)

ODS 12: Producción y consumo responsables(1)

ODS 13: Acción por el clima(1)

ODS 17: Alianzas para lograr los objetivos(1)

Año de Publicación

Origen

Palabras Claves

Approximate Bayesian Computation(2)

uncertainty quantification(2)

Bayesian Neural Network(1)

Gradient-free training(1)

Hybrid models(1)

Physics-guided Bayesian neural networks by ABC-SS: Application to reinforced concrete columns

Abstract: This manuscript proposes a physics-guided Bayesian neural network, which combines Approximate-Bayesi

Palabras claves:

Approximate Bayesian Computation, Hybrid models, Physics-guided neural networks, Shear-capacity evaluation, uncertainty quantification

Corbetta M., Fernández J., José Barros, Juan Chiachío, Ruano M.C.

Uncertainty quantification in Neural Networks by Approximate Bayesian Computation: Application to fatigue in composite materials

Abstract: Modern machine learning algorithms excel in a great variety of tasks, but at the same time, it is al

Palabras claves:

Approximate Bayesian Computation, Bayesian Neural Network, Gradient-free training, Non-parametric formulation, Subset simulation, uncertainty quantification

Fernández J., Herrera F., Juan Chiachío, Munoz R., Ruano M.C.