Path Planning for Reconfigurable hTetro Robot Combining Heat Conduction-Based and Discrete Optimization. - Huy Do; Anh Vu Le; Oliver Weeger; Rajesh Elara Mohan; Yujie Guo; Tan N. Nguyen; Minh Bui Vu; Van Duc Phan (IEEE Access, 2021)

Polyconvex anisotropic hyperelasticity with neural networks. - Dominik K. Klein; Mauricio Fernández; Robert J. Martin; Patrizio Neff; Oliver Weeger (CoRR, 2021)

KnitKit: a flexible system for machine knitting of customizable textiles. - Georges Nader; Yu Han Quek; Pei Zhi Chia; Oliver Weeger; Sai-Kit Yeung (ACM Trans. Graph., 2021)

Finite electro-elasticity with physics-augmented neural networks. - Dominik K. Klein; Rogelio Ortigosa; Jesús Martínez-Frutos; Oliver Weeger (CoRR, 2022)

How to Build the Optimal Magnet Assembly for Magnetocaloric Cooling: Structural Optimization with Isogeometric Analysis. - Michael Wiesheu; Melina Merkel; Tim Sittig; Dimitri Benke; Max Fries; Sebastian Schöps; Oliver Weeger; Idoia Cortes Garcia (CoRR, 2022)

Heat conduction combined grid-based optimization method for reconfigurable pavement sweeping robot path planning. - Huy Do; Anh Vu Le; Lim Yi; Joel Chan Cheng Hoong; Minh Tran 001; Van Duc Phan; Minh Bui Vu; Oliver Weeger; Rajesh Elara Mohan (Robotics Auton. Syst., 2022)

Neural networks meet hyperelasticity: A guide to enforcing physics. - Lennart Linden; Dominik K. Klein; Karl A. Kalina; Jörg Brummund; Oliver Weeger; Markus Kästner (CoRR, 2023)

Advanced discretization techniques for hyperelastic physics-augmented neural networks. - Marlon Franke; Dominik K. Klein; Oliver Weeger; Peter Betsch (CoRR, 2023)

Parametrised polyconvex hyperelasticity with physics-augmented neural networks. - Dominik K. Klein; Fabian J. Roth; Iman Valizadeh; Oliver Weeger (CoRR, 2023)

A robust finite strain isogeometric solid-beam element. - Abdullah Shafqat; Oliver Weeger; Bai-Xiang Xu (CoRR, 2023)

Nonlinear electro-elastic finite element analysis with neural network constitutive models. - Dominik K. Klein; Rogelio Ortigosa; Jesús Martínez-Frutos; Oliver Weeger (CoRR, 2024)

Physics-augmented neural networks for constitutive modeling of hyperelastic geometrically exact beams. - Jasper O. Schommartz; Dominik K. Klein; Juan C. Alzate Cobo; Oliver Weeger (CoRR, 2024)

TwinLab: a framework for data-efficient training of non-intrusive reduced-order models for digital twins. - Maximilian Kannapinn; Michael Schäfer 004; Oliver Weeger (CoRR, 2024)

Multiscale topology optimization of functionally graded lattice structures based on physics-augmented neural network material models. - Jonathan Stollberg; Tarun Gangwar; Oliver Weeger; Dominik Schillinger (CoRR, 2024)

Digital twin inference from multi-physical simulation data of DED additive manufacturing processes with neural ODEs. - Maximilian Kannapinn; Fabian J. Roth; Oliver Weeger (CoRR, 2024)

Multiscale modeling of functionally graded shell lattice metamaterials for additive manufacturing. - Mohammad Shojaee; Iman Valizadeh; Dominik K. Klein; P. Sharifi; Oliver Weeger (Eng. Comput., 2024)

Machine Learning with Physics Knowledge for Prediction: A Survey. - Joe Watson; Chen Song; Oliver Weeger; Theo Gruner; An Thai Le 001; Kay Hansel; Ahmed Hendawy; Oleg Arenz; Will Trojak; Miles D. Cranmer; Carlo D'Eramo; Fabian Bülow; et al. (Trans. Mach. Learn. Res., 2025)

Stable Port-Hamiltonian Neural Networks. - Fabian J. Roth; Dominik K. Klein; Maximilian Kannapinn; Jan Peters 001; Oliver Weeger (CoRR, 2025)

Physics-based Machine Learning for Computational Fracture Mechanics. - Fadi Aldakheel; Elsayed S. Elsayed; Yousef Heider; Oliver Weeger (CoRR, 2025)