Software
Filippo Masi
Research Scientist | Inria, TRIPOP project-team, Univ. Grenoble Alpes
Main projects
NICE — Neural Integration for Constitutive Equations
A deep-learning framework for the automatic discovery of constitutive equations from small, sparse and incomplete material-state observations.
Thermodynamics-based Artificial Neural Networks
Reference implementation of thermodynamics-based neural architectures for constitutive modelling of inelastic materials.
TANN-multiscale
Micromechanical simulations, training workflows and finite-element examples for multiscale modelling of inelastic materials with TANN.
Constitutive transport learning
Hard-constrained thermodynamic learning of inelastic constitutive models from stress–strain data through generalised transport operators.