Computational Modelling of Micromorphic Continua - Theory, Numerics, and Visualisation Challenges. - C. Britta Hirschberger; Ellen Kuhl; Paul Steinmann (VLUDS, 2006)

On Discrete Modeling and Visualization of Granular Media. - Holger A. Meier; Ellen Kuhl; Paul Steinmann (VLUDS, 2006)

A discontinuous Galerkin method for the Cahn-Hilliard equation. - Garth N. Wells; Ellen Kuhl; Krishna C. Garikipati (J. Comput. Phys., 2006)

Towards Completeness, a Multiscale Approach of Confined Particulate Systems. - Holger A. Meier; Paul Steinmann; Ellen Kuhl (Visualization of Large and Unstructured Data Sets, 2007)

Visualization of Particle Interactions in Granular Media. - Holger A. Meier; Michael Schlemmer; Christian Wagner 010; Andreas Kerren; Hans Hagen; Ellen Kuhl; Paul Steinmann (IEEE Trans. Vis. Comput. Graph., 2008)

Imaging-Based Computation of the Dynamics of Pelvic Floor Deformation and Strain Visualization Analysis. - Christos E. Constantinou; Linda McLean; Ellen Kuhl; Bertha Chen (ISVC (3), 2010)

Human pluripotent stem cell tools for cardiac optogenetics. - Yan Zhuge; Bhagat Patlolla; Charu Ramakrishnan; Ramin E. Beygui; Christopher K. Zarins; Karl Deisseroth; Ellen Kuhl; Oscar J. Abilez (EMBC, 2014)

Towards an instrumented tissue expander. - Annette I. Bohmer; Alexander M. Zollner; Ellen Kuhl; Udo Lindemann (IEEM, 2014)

A New Sparse Matrix Vector Multiplication GPU Algorithm Designed for Finite Element Problems. - Jonathan Wong; Ellen Kuhl; Eric Darve (CoRR, 2015)

Multi-fidelity classification using Gaussian processes: accelerating the prediction of large-scale computational models. - Francisco Sahli Costabal; Paris Perdikaris; Ellen Kuhl; Daniel E. Hurtado (CoRR, 2019)

Integrating machine learning and multiscale modeling - perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences. - Mark S. Alber; Adrian Buganza Tepole; William R. Cannon; Suvranu De; Salvador Dura-Bernal; Krishna C. Garikipati; George E. Karniadakis; William W. Lytton; Paris Perdikaris; Linda R. Petzold; Ellen Kuhl (npj Digit. Medicine, 2019)

Protein-protein interactions in neurodegenerative diseases: A conspiracy theory. - Travis B. Thompson; Pavanjit Chaggar; Ellen Kuhl; Alain Goriely; Alzheimer's Disease Neuroimaging Initiative (PLoS Comput. Biol., 2020)

A Framework for Evaluating Myocardial Stiffness Using 3D-Printed Heart Phantoms. - Fikunwa O. Kolawole; Mathias Peirlinck; Tyler E. Cork; Vicky Y. Wang; Seraina Anne Dual; Marc E. Levenston; Ellen Kuhl; Daniel B. Ennis (FIMH, 2021)

Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems. - Kevin Linka; Amelie Schäfer; Xuhui Meng; Zongren Zou; George Em Karniadakis; Ellen Kuhl (CoRR, 2022)

A new family of Constitutive Artificial Neural Networks towards automated model discovery. - Kevin Linka; Ellen Kuhl (CoRR, 2022)

Physics-guided deep learning for data scarcity. - Jinshuai Bai; Laith Alzubaidi; Qingxia Wang; Ellen Kuhl; Mohammed Bennamoun; Yuantong Gu (CoRR, 2022)

Correlating tau pathology to brain atrophy using a physics-based Bayesian model. - Amelie Schäfer; Pavanjit Chaggar; Alain Goriely; Ellen Kuhl (Eng. Comput., 2022)

Evaluating Passive Myocardial Stiffness Using in vivo cine, cDTI, and Tagged MRI. - Fikunwa O. Kolawole; Vicky Y. Wang; Bianca Freytag; Michael Loecher; Tyler E. Cork; Martyn P. Nash; Ellen Kuhl; Daniel B. Ennis (FIMH, 2023)

Benchmarks for physics-informed data-driven hyperelasticity. - Vahidullah Tac; Kevin Linka; Francisco Sahli Costabal; Ellen Kuhl; Adrian Buganza Tepole (CoRR, 2023)

Discovering a reaction-diffusion model for Alzheimer's disease by combining PINNs with symbolic regression. - Zhen Zhang 029; Zongren Zou; Ellen Kuhl; George Em Karniadakis (CoRR, 2023)

On sparse regression, Lp-regularization, and automated model discovery. - Jeremy A. McCulloch; Skyler R. St. Pierre; Kevin Linka; Ellen Kuhl (CoRR, 2023)

Theory and implementation of inelastic Constitutive Artificial Neural Networks. - Hagen Holthusen; Lukas Lamm; Tim Brepols; Stefanie Reese; Ellen Kuhl (CoRR, 2023)

A Simulation Tool for Physics-Informed Control of Biomimetic Soft Robotic Arms. - Bartosz Kaczmarski; Alain Goriely; Ellen Kuhl; Derek E. Moulton (IEEE Robotics Autom. Lett., 2023)

Automated Data-Driven Discovery of Material Models Based on Symbolic Regression: A Case Study on Human Brain Cortex. - Jixin Hou; Xianyan Chen; Taotao Wu; Ellen Kuhl; Xianqiao Wang (CoRR, 2024)

Minimal activation with maximal reach: Reachability clouds of bio-inspired slender manipulators. - Bartosz Kaczmarski; Derek E. Moulton; Alain Goriely; Ellen Kuhl (CoRR, 2024)

Atrial Constitutive Neural Networks. - Mathias Peirlinck; Kevin Linka; Ellen Kuhl (FIMH (1), 2025)

Automated model discovery for tensional homeostasis: Constitutive machine learning in growth and remodeling. - Hagen Holthusen; Tim Brepols; Kevin Linka; Ellen Kuhl (Comput. Biol. Medicine, 2025)

A generalized dual potential for inelastic Constitutive Artificial Neural Networks: A JAX implementation at finite strains. - Hagen Holthusen; Kevin Linka; Ellen Kuhl; Tim Brepols (CoRR, 2025)

Discovering uncertainty: Gaussian constitutive neural networks with correlated weights. - Jeremy A. McCulloch; Ellen Kuhl (CoRR, 2025)

A universal material model subroutine for soft matter systems. - Mathias Peirlinck; Juan A. Hurtado; Manuel K. Rausch; Adrian Buganza Tepole; Ellen Kuhl (Eng. Comput., 2025)

Non-smooth optimization meets automated material model discovery. - Moritz Flaschel; Trevor Hastie; Ellen Kuhl (CoRR, 2025)

Material Fingerprinting: A shortcut to material model discovery without solving optimization problems. - Moritz Flaschel; Denisa Martonova; Carina Veil; Ellen Kuhl (CoRR, 2025)