A simple algorithm for the fast calculation of higher order derivatives of the inverse function. - Roozbeh Dargazany; Karl Hörnes; Mikhail Itskov (Appl. Math. Comput., 2013)

An analysis on the shear modulus of the modified Jeffreys model. - Hilbeth P. Azikri de Deus; Thales A. Barbosa Pinto Silva; Mikhail Itskov (Appl. Math. Comput., 2019)

A general theory for anisotropic Kirchhoff-Love shells with embedded fibers and in-plane bending. - Thang Xuan Duong; Vu Ngoc Khiêm; Mikhail Itskov; Roger Andrew Sauer (CoRR, 2021)

A general isogeometric finite element formulation for rotation-free shells with embedded fibers and in-plane bending. - Thang Xuan Duong; Mikhail Itskov; Roger Andrew Sauer (CoRR, 2021)

Constitutive artificial neural networks: A fast and general approach to predictive data-driven constitutive modeling by deep learning. - Kevin Linka; Markus Hillgärtner; Kian P. Abdolazizi; Roland C. Aydin; Mikhail Itskov; Christian J. Cyron (J. Comput. Phys., 2021)

Automatic generation of interpretable hyperelastic material models by symbolic regression. - Rasul Abdusalamov; Markus Hillgärtner; Mikhail Itskov (CoRR, 2022)

Discovering Asymptotic Expansions Using Symbolic Regression. - Rasul Abdusalamov; Julius Kaplunov; Mikhail Itskov (CoRR, 2023)

Physics-Informed Quantum Machine Learning for Solving Partial Differential Equations. - Abhishek Setty; Rasul Abdusalamov; Mikhail Itskov (CoRR, 2023)

Rediscovering the Mullins Effect With Deep Symbolic Regression. - Rasul Abdusalamov; Jendrik Weise; Mikhail Itskov (CoRR, 2024)

Rediscovering Hyperelasticity by Deep Symbolic Regression. - Rasul Abdusalamov; Mikhail Itskov (CoRR, 2025)