Machine Learning methods and, in particular, Artificial Neural Networks (ANNs) have demonstrated promising capabilities material constitutive modeling. One of the main drawbacks such approaches is lack a rigorous frame based on laws physics. This may render physically inconsistent predictions trained network, which can be even dangerous for real applications. Here we propose new class data-driv...
