Geodesic

Tome 73 (2023)

Sommaire

Editorial of CEMRACS 2021
p. 1
Comparison of statistical, machine learning, and mathematical modelling methods to investigate the effect of ageing on dog’s cardiovascular system
p. 2-27
Wasserstein model reduction approach for parametrized flow problems in porous media
p. 28-47
Deep learning-based schemes for singularly perturbed convection-diffusion problems
p. 48-67
Parametrized non intrusive space-time approximation for explicit dynamic fem applications
p. 68-88
A component-based data assimilation strategy with applications to vascular flows
p. 89-106
On basis set optimisation in quantum chemistry
p. 107-129
Mortensen observer for a class of variational inequalities – lost equivalence with stochastic filtering approaches
p. 130-157
Impact of physical model error on state estimation for neutronics applications
p. 158-172
Computation of the self-diffusion coefficient with low-rank tensor methods: application to the simulation of a cross-diffusion system
p. 173-186
Accelerating metabolic models evaluation with statistical metamodels: application to Salmonella infection models
p. 187-217
Efficient approximations of the fisher matrix in neural networks using kronecker product singular value decomposition
p. 218-237
Generative methods for sampling transition paths in molecular dynamics
p. 238-256