Recurrent Neural Networks for Uncertain Time-Dependent Structural Behavior. - Wolfgang Graf; Steffen Freitag; Michael Kaliske; Jan-Uwe Sickert (Comput. Aided Civ. Infrastructure Eng., 2010)

Recurrent neural networks for fuzzy data. - Steffen Freitag; Wolfgang Graf; Michael Kaliske (Integr. Comput. Aided Eng., 2011)

Structural Analysis with Fuzzy Data and Neural Network Based Material Description. - Wolfgang Graf; Steffen Freitag; Jan-Uwe Sickert; Michael Kaliske (Comput. Aided Civ. Infrastructure Eng., 2012)

Computational Intelligence for Efficient Numerical Design of Structures with Uncertain Parameters. - Wolfgang Graf; Marco Götz; Ferenc Leichsenring; Michael Kaliske (SSCI, 2015)

Spiking response model for uniaxial carbon concrete experimental data. - Ferenc Leichsenring; Wolfgang Graf; Michael Kaliske (SSCI, 2016)

Computing permissible design spaces under consideration of functional responses. - Wolfgang Graf; Marco Götz; Michael Kaliske (Adv. Eng. Softw., 2018)

Artificial Neural Networks Based Friction Law for Elastomeric Materials Applied in Finite Element Sliding Contact Simulations. - Aleksandra Serafinska; Wolfgang Graf; Michael Kaliske (Complex., 2018)

ELSA: An efficient, adaptive Ensemble Learning-based Sampling Approach. - Maria Böttcher; Alexander Fuchs 010; Ferenc Leichsenring; Wolfgang Graf; Michael Kaliske (Adv. Eng. Softw., 2021)

Robustness versus Performance - Nested Inherence of Objectives in Optimization with Polymorphic Uncertain Parameters. - F. Niklas Schietzold; Ferenc Leichsenring; Marco Götz; Wolfgang Graf; Michael Kaliske (Adv. Eng. Softw., 2021)

A comparative study of fully implicit staggered and monolithic solution methods. Part I: Coupled bidomain equations of cardiac electrophysiology. - Baris Cansiz; Michael Kaliske (J. Comput. Appl. Math., 2022)

Mixed formulation of physics-informed neural networks for thermo-mechanically coupled systems and heterogeneous domains. - Ali Harandi; Ahmad Moeineddin; Michael Kaliske; Stefanie Reese; Shahed Rezaei (CoRR, 2023)

Fast and Reliable Reduced-Order Models for Cardiac Electrophysiology. - Sridhar Chellappa; Baris Cansiz; Lihong Feng; Peter Benner; Michael Kaliske (CoRR, 2023)

Integration of physics-informed operator learning and finite element method for parametric learning of partial differential equations. - Shahed Rezaei; Ahmad Moeineddin; Michael Kaliske; Markus Apel (CoRR, 2024)

Finite Operator Learning: Bridging Neural Operators and Numerical Methods for Efficient Parametric Solution and Optimization of PDEs. - Shahed Rezaei; Reza Najian Asl; Kianoosh Taghikhani; Ahmad Moeineddin; Michael Kaliske; Markus Apel (CoRR, 2024)

A comparative study of fully implicit staggered and monolithic solution methods. Part II: Coupled excitation-contraction equations of cardiac electromechanics. - Baris Cansiz; Michael Kaliske (J. Comput. Appl. Math., 2024)

Influence of left ventricle longitudinal axis translation on rotation measurements in 3D echocardiography. - Baris Cansiz; Krunoslav Michael Sveric; Jens Fassl; Axel Linke; Michael Kaliske (Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2024)

Assessment of LV structural remodelling by the application of the finite element method to 3D echocardiography data. - Yongjae Lee; Baris Cansiz; Krunoslav Michael Sveric; Axel Linke; Michael Kaliske (Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2024)

Intermediately discretized extended α-level-optimization - An advanced fuzzy analysis approach. - Bertram Richter; F. Niklas Schietzold; Wolfgang Graf; Michael Kaliske (Adv. Eng. Softw., 2025)

Simulation of parametrized cardiac electrophysiology in three dimensions using physics-informed neural networks. - Roshan Antony Gomez; Julien Stöcker; Baris Cansiz; Michael Kaliske (CoRR, 2025)