| Modeling and simulation of the aggregation and the structural and mechanical properties of silica aerogels R Abdusalamov, C Scherdel, M Itskov, B Milow, G Reichenauer, A Rege The Journal of Physical Chemistry B 125 (7), 1944-1950, 2021 | 37 | 2021 |
| Automatic generation of interpretable hyperelastic material models by symbolic regression R Abdusalamov, M Hillgärtner, M Itskov International Journal for Numerical Methods in Engineering 124 (9), 2093-2104, 2023 | 16 | 2023 |
| Machine learning-based structure–property predictions in silica aerogels R Abdusalamov, P Pandit, B Milow, M Itskov, A Rege Soft matter 17 (31), 7350-7358, 2021 | 14 | 2021 |
| Investigation of the fractal properties of aerogels by diffusion-limited aggregation models R Abdusalamabov, M Itskov, B Milow, G Reichenauer, A Rege Proceedings of the 8th GACM Colloquium on Computational Mechanics: For Young …, 2019 | 3 | 2019 |
| Hyperelastic material modelling using symbolic regression R Abdusalamov, M Hillgärtner, M Itskov PAMM 22 (1), e202200263, 2023 | 2 | 2023 |
| Deep reinforcement learning for microstructural optimisation of silica aerogels P Pandit, R Abdusalamov, M Itskov, A Rege Scientific Reports 14 (1), 1511, 2024 | 1 | 2024 |
| Discovering asymptotic expansions for problems in mechanics using symbolic regression R Abdusalamov, J Kaplunov, M Itskov Mechanics Research Communications 133, 104197, 2023 | 1 | 2023 |
| Data‐driven inverse design and optimisation of silica aerogel model networks P Pandit, R Abdusalamov, M Itskov, B Milow, A Rege PAMM 23 (1), e202200329, 2023 | 1 | 2023 |
| Adjustment of micro-structure parameters of aggregated structures for dynamic modeling of silica aerogels R Abdusalamov, M Itskov, J Kaplunov, D Prikazchikov Mechanics of High-Contrast Elastic Solids: Contributions from Euromech …, 2023 | 1 | 2023 |
| A mesoscale model of non‐crimp fabrics based on a deep learning framework S Zhou, M Hillgärtner, R Abdusalamov, T X. Duong, M Itskov PAMM 22 (1), e202200298, 2023 | 1 | 2023 |
| Analysis of the fractal properties of silica aerogels using diffusion‐limited aggregation R Abdusalamov, M Itskov, B Milow, A Rege PAMM 20 (1), e202000099, 2021 | 1 | 2021 |
| Rediscovering the Mullins Effect With Deep Symbolic Regression R Abdusalamov, J Weise, M Itskov arXiv preprint arXiv:2403.05495, 2024 | | 2024 |
| Analysis of the microstructural connectivity and compressive behavior of particle aggregated silica aerogels W Xiong, R Abdusalamov, M Itskov, B Milow, A Rege PAMM, e202300224, 2024 | | 2024 |
| Physics-Informed Quantum Machine Learning for Solving Partial Differential Equations A Setty, R Abdusalamov, M Itskov arXiv preprint arXiv:2312.09215, 2023 | | 2023 |
| Reinforcement Learning For Inverse Design Of Porous Materials P Pandit, R Abdusalamov, AG Rege | | 2023 |
| Discovering Asymptotic Expansions Using Symbolic Regression R Abdusalamov, J Kaplunov, M Itskov arXiv preprint arXiv:2307.01876, 2023 | | 2023 |
| Predictive modeling and simulation of silica aerogels by using aggregation algorithms R Abdusalamov, P Pandit, M Itskov, B Milow, A Rege PAMM 21 (1), e202100165, 2021 | | 2021 |
| Understanding the influence of morphology on the fractal and mechanical properties of silica aerogels R Abdusalamov, C Scherdel, M Itskov, B Milow, G Reichenauer, A Rege | | 2020 |
| Modeling of Softening Behavior by Deep Symbolic Regression M Itskov, R Abdusalamov | | |
| Discovering Asymptotic Expansions Using Symbolic Regression in Mechanics R Abdusalamov, J Kaplunov, M Itskov Available at SSRN 4559957, 0 | | |
