2 citations · 3 across the 3 of their papers we have counts for
4 papers
Modelling spatiotemporal turbulent dynamics with the convolutional autoencoder echo state network
Alberto Racca, Nguyen Anh Khoa Doan, Luca Magri
The spatiotemporal dynamics of turbulent flows is chaotic and difficult to predict. This makes the design of accurate and stable reduced-order models challenging. The overarching o…
Data-driven prediction and control of extreme events in a chaotic flow
Alberto Racca, Luca Magri
An extreme event is a sudden and violent change in the state of a nonlinear system. In fluid dynamics, extreme events can have adverse effects on the system's optimal design and op…
Robust Optimization and Validation of Echo State Networks for learning chaotic dynamics
Alberto Racca, Luca Magri
An approach to the time-accurate prediction of chaotic solutions is by learning temporal patterns from data. Echo State Networks (ESNs), which are a class of Reservoir Computing, c…
Automatic-differentiated Physics-Informed Echo State Network (API-ESN)
Alberto Racca, Luca Magri
We propose the Automatic-differentiated Physics-Informed Echo State Network (API-ESN). The network is constrained by the physical equations through the reservoir's exact time-deriv…