Search Results for author:
Found 2 papers, 0 papers with code
GN-SINDy: Greedy Sampling Neural Network in Sparse Identification of Nonlinear Partial Differential Equations
In this paper, we extend the results of a SINDy based deep learning model discovery (DeePyMoD) approach by integrating greedy sampling technique in its data collection unit and new sparsity promoting algorithms in the least squares minimization unit.
A Robust SINDy Approach by Combining Neural Networks and an Integral Form
To do this, we make use of neural networks to learn an implicit representation based on measurement data so that not only it produces the output in the vicinity of the measurements but also the time-evolution of output can be described by a dynamical system.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
