| Biomechanical rupture risk assessment of abdominal aortic aneurysms using clinical data: A patient-specific, probabilistic framework and comparative case-control study L Bruder, J Pelisek, HH Eckstein, MW Gee Plos one 15 (11), e0242097, 2020 | 16 | 2020 |
| Beyond black-boxes in Bayesian inverse problems and model validation: applications in solid mechanics of elastography L Bruder, PS Koutsourelakis International Journal for Uncertainty Quantification 8 (5), 447-482, 2018 | 11 | 2018 |
| Data-consistent Solutions to Stochastic Inverse Problems using a Probabilistic Multi-fidelity Method Based on Conditional Densities L Bruder, MW Gee, T Wildey International Journal for Uncertainty Quantification 10 (5), 399-424, 2020 | 2 | 2020 |
| Methoden der künstlichen Intelligenz in der vaskulären Medizin L Bruder, B Reutersberg, M Bassilious, W Schüttler, HH Eckstein, ... Gefässchirurgie 24 (7), 539-547, 2019 | 2 | 2019 |
| Changes in endocan and dermatan sulfate are associated with biomechanical properties of abdominal aortic wall during aneurysm expansion and rupture S Metschl, L Bruder, V Paloschi, K Jakob, B Reutersberg, C Reeps, ... Thrombosis and haemostasis, 2022 | 1 | 2022 |
| Biomechanical assessment of abdominal aortic aneurysm rupture risk and growth using clinical data: a probabilistic approach L Bruder Technische Universität München, 2022 | | 2022 |
| Moving Beyond Forward Simulation to Enable Data-informed Physics-based Predictions. TM Wildey, L Bruder, T Bui-Thanh, T Butler, JD Jakeman, B Marvin, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2019 | | 2019 |
| Solving Stochastic Inverse Problems using Approximate Push-forward Densities based on a Multi-fidelity Monte Carlo Method. TM Wildey, T Butler, JD Jakeman, L Bruder Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2019 | | 2019 |
| Developing Scalable and Multi-fidelity Approaches for Push-forward Based Inference. TM Wildey, T Butler, JD Jakeman, T Bui-Thanh, B Marvin, L Bruder Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2019 | | 2019 |
Michael W. GeeProfessor Mechanics & High Performance Computing, TU Munich, GermanyVerified email at tum.de
