11 citations · 11 across the 4 of their papers we have counts for
5 papers
Rediscovering Hyperelasticity by Deep Symbolic Regression
Rasul Abdusalamov, Mikhail Itskov
The accurate modeling of the mechanical behavior of rubber-like materials under multi-axial loading constitutes a long-standing challenge in hyperelastic material modeling. This wo…
Rediscovering the Mullins Effect With Deep Symbolic Regression
Rasul Abdusalamov, Jendrik Weise, Mikhail Itskov
The Mullins effect represents a softening phenomenon observed in rubber-like materials and soft biological tissues. It is usually accompanied by many other inelastic effects like f…
Self-Adaptive Physics-Informed Quantum Machine Learning for Solving Differential Equations
Abhishek Setty, Rasul Abdusalamov, Felix Motzoi
Chebyshev polynomials have shown significant promise as an efficient tool for both classical and quantum neural networks to solve linear and nonlinear differential equations. In th…
Discovering Asymptotic Expansions Using Symbolic Regression
Rasul Abdusalamov, Julius Kaplunov, Mikhail Itskov
Recently, symbolic regression (SR) has demonstrated its efficiency for discovering basic governing relations in physical systems. A major impact can be potentially achieved by coup…
Automatic generation of interpretable hyperelastic material models by symbolic regression
Rasul Abdusalamov, Markus Hillgärtner, Mikhail Itskov
In this paper, we present a new procedure to automatically generate interpretable hyperelastic material models. This approach is based on symbolic regression which represents an ev…