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2020 – today
- 2024
[j10]Yongjae Lee
, Baris Cansiz, Krunoslav Michael Sveric, Axel Linke, Michael Kaliske:
Assessment of LV structural remodelling by the application of the finite element method to 3D echocardiography data. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 12(1) (2024)- [j9]Baris Cansiz, Michael Kaliske:
A comparative study of fully implicit staggered and monolithic solution methods. Part II: Coupled excitation-contraction equations of cardiac electromechanics. J. Comput. Appl. Math. 442: 115704 (2024) - [i4]Shahed Rezaei, Ahmad Moeineddin, Michael Kaliske, Markus Apel:
Integration of physics-informed operator learning and finite element method for parametric learning of partial differential equations. CoRR abs/2401.02363 (2024) - [i3]Shahed Rezaei, Reza Najian Asl, Kianoosh Taghikhani, Ahmad Moeineddin, Michael Kaliske, Markus Apel:
Finite Operator Learning: Bridging Neural Operators and Numerical Methods for Efficient Parametric Solution and Optimization of PDEs. CoRR abs/2407.04157 (2024) - 2023
- [i2]Ali Harandi, Ahmad Moeineddin, Michael Kaliske, Stefanie Reese, Shahed Rezaei:
Mixed formulation of physics-informed neural networks for thermo-mechanically coupled systems and heterogeneous domains. CoRR abs/2302.04954 (2023) - [i1]Sridhar Chellappa, Baris Cansiz, Lihong Feng, Peter Benner, Michael Kaliske:
Fast and Reliable Reduced-Order Models for Cardiac Electrophysiology. CoRR abs/2311.06164 (2023) - 2022
- [j8]Baris Cansiz, Michael Kaliske:
A comparative study of fully implicit staggered and monolithic solution methods. Part I: Coupled bidomain equations of cardiac electrophysiology. J. Comput. Appl. Math. 407: 114021 (2022) - 2021
- [j7]Maria Böttcher, Alexander Fuchs, Ferenc Leichsenring, Wolfgang Graf, Michael Kaliske:
ELSA: An efficient, adaptive Ensemble Learning-based Sampling Approach. Adv. Eng. Softw. 154: 102974 (2021) - [j6]F. Niklas Schietzold, Ferenc Leichsenring, Marco Götz, Wolfgang Graf, Michael Kaliske:
Robustness versus Performance - Nested Inherence of Objectives in Optimization with Polymorphic Uncertain Parameters. Adv. Eng. Softw. 156: 102932 (2021)
2010 – 2019
- 2018
- [j5]Wolfgang Graf, Marco Götz, Michael Kaliske:
Computing permissible design spaces under consideration of functional responses. Adv. Eng. Softw. 117: 95-106 (2018) - [j4]Aleksandra Serafinska, Wolfgang Graf, Michael Kaliske:
Artificial Neural Networks Based Friction Law for Elastomeric Materials Applied in Finite Element Sliding Contact Simulations. Complex. 2018: 4396758:1-4396758:15 (2018) - 2016
- [c2]Ferenc Leichsenring, Wolfgang Graf, Michael Kaliske:
Spiking response model for uniaxial carbon concrete experimental data. SSCI 2016: 1-6 - 2015
- [c1]Wolfgang Graf, Marco Götz, Ferenc Leichsenring, Michael Kaliske:
Computational Intelligence for Efficient Numerical Design of Structures with Uncertain Parameters. SSCI 2015: 1824-1831 - 2012
- [j3]Wolfgang Graf, Steffen Freitag, Jan-Uwe Sickert, Michael Kaliske:
Structural Analysis with Fuzzy Data and Neural Network Based Material Description. Comput. Aided Civ. Infrastructure Eng. 27(9): 640-654 (2012) - 2011
- [j2]Steffen Freitag, Wolfgang Graf, Michael Kaliske:
Recurrent neural networks for fuzzy data. Integr. Comput. Aided Eng. 18(3): 265-280 (2011) - 2010
- [j1]Wolfgang Graf, Steffen Freitag, Michael Kaliske, Jan-Uwe Sickert:
Recurrent Neural Networks for Uncertain Time-Dependent Structural Behavior. Comput. Aided Civ. Infrastructure Eng. 25(5): 322-323 (2010)
Coauthor Index
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