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GitHub / oselin / gradient_ML_LTI
A gentle introduction to custom gradient propagation for ML application in which parameters of LTI systems have to be optimized. This example enables the integration of control theory with machine learning, for the development of Physical-Informed Neural Networks (PINNs)
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Forks: 0
Open Issues: 0
License: mit
Language: Jupyter Notebook
Repo Size: 1.95 MB
Dependencies:
0
Created: 4 months ago
Updated: 4 months ago
Last pushed: 3 months ago
Last synced: 3 months ago
Topics: backward-propagation, gradient-descent, laplace, lti, machine-learning, torch
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