Comptes Rendus

Numéro spécial

Data-Based Engineering Science and Technology

Numéro thématique coordonné par : Francisco Chinesta ;  Elias Cueto ;  Pierre Ladevèze

Sommaire

Editorial Board
p. IFC
Foreword
p. 741
Direct numerical simulation of flexible molecules and data-driven molecular conformation
p. 743-753
Code2vect: An efficient heterogenous data classifier and nonlinear regression technique
p. 754-761
Real-time Bayesian data assimilation with data selection, correction of model bias, and on-the-fly uncertainty propagation
p. 762-779
Incremental dynamic mode decomposition: A reduced-model learner operating at the low-data limit
p. 780-792
Nonintrusive data-based learning of a switched control heating system using POD, DMD and ANN
p. 793-805
An efficient Tabu-search optimized regression for data-driven modeling
p. 806-816
Risk analysis: Survival data analysis vs. machine learning. Application to Alzheimer prediction
p. 817-830
Data-driven computation for history-dependent materials
p. 831-844
Data-driven modeling and learning in science and engineering
p. 845-855
Evaluation of hip fracture risk using a hyper-parametric model based on the Locally Linear Embedding technique
p. 856-862
Modal decomposition from partial measurements
p. 863-872
A non-intrusive approach for the reconstruction of POD modal coefficients through active subspaces
p. 873-881
Identification of nonlinear dynamical system equations using dynamic mode decomposition under invariant quantity constraints
p. 882-890
Editorial Board
p. IBC