Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 2064 | 2018 |
Multiphysics simulations: Challenges and opportunities DE Keyes, LC McInnes, C Woodward, W Gropp, E Myra, M Pernice, J Bell, ... The International Journal of High Performance Computing Applications 27 (1 …, 2013 | 516 | 2013 |
Space-filling curves: an introduction with applications in scientific computing M Bader Springer Science & Business Media, 2012 | 415 | 2012 |
preCICE–a fully parallel library for multi-physics surface coupling HJ Bungartz, F Lindner, B Gatzhammer, M Mehl, K Scheufele, A Shukaev, ... Computers & Fluids 141, 250-258, 2016 | 374 | 2016 |
Peano—a traversal and storage scheme for octree-like adaptive Cartesian multiscale grids T Weinzierl, M Mehl SIAM Journal on Scientific Computing 33 (5), 2732-2760, 2011 | 120 | 2011 |
Parallel coupling numerics for partitioned fluid–structure interaction simulations M Mehl, B Uekermann, H Bijl, D Blom, B Gatzhammer, A Van Zuijlen Computers & Mathematics with Applications 71 (4), 869-891, 2016 | 114 | 2016 |
preCICE v2: A sustainable and user-friendly coupling library G Chourdakis, K Davis, B Rodenberg, M Schulte, F Simonis, ... Open Research Europe 2, 2022 | 110 | 2022 |
A cache-aware algorithm for PDEs on hierarchical data structures based on space-filling curves F Günther, M Mehl, M Pögl, C Zenger SIAM Journal on Scientific Computing 28 (5), 1634-1650, 2006 | 93 | 2006 |
The PDE framework Peano applied to fluid dynamics: an efficient implementation of a parallel multiscale fluid dynamics solver on octree-like adaptive Cartesian grids HJ Bungartz, M Mehl, T Neckel, T Weinzierl Computational Mechanics 46, 103-114, 2010 | 86 | 2010 |
Improving the performance of the partitioned QN-ILS procedure for fluid–structure interaction problems: Filtering R Haelterman, AEJ Bogaers, K Scheufele, B Uekermann, M Mehl Computers & Structures 171, 9-17, 2016 | 70 | 2016 |
A cache‐oblivious self‐adaptive full multigrid method M Mehl, T Weinzierl, C Zenger Numerical Linear Algebra with Applications 13 (2‐3), 275-291, 2006 | 59 | 2006 |
A parallel adaptive Cartesian PDE solver using space–filling curves HJ Bungartz, M Mehl, T Weinzierl European Conference on Parallel Processing, 1064-1074, 2006 | 51 | 2006 |
A comparison of various quasi-Newton schemes for partitioned fluid-structure interaction F Lindner, M Mehl, K Scheufele, B Uekermann Coupled VI: Proceedings of the VI International Conference on Computational …, 2015 | 48 | 2015 |
Numerical simulation of particle transport in a drift ratchet M Brenk, HJ Bungartz, M Mehl, IL Muntean, T Neckel, T Weinzierl SIAM Journal on Scientific Computing 30 (6), 2777-2798, 2008 | 46 | 2008 |
Reinforcement learning for call admission control and routing in integrated service networks P Marbach, O Mihatsch, M Schulte, J Tsitsiklis Advances in Neural Information Processing Systems 10, 1997 | 44 | 1997 |
Fluid-structure interaction on cartesian grids: Flow simulation and coupling environment M Brenk, HJ Bungartz, M Mehl, T Neckel Fluid-Structure Interaction: Modelling, Simulation, Optimisation, 233-269, 2006 | 43 | 2006 |
Where did the tumor start? An inverse solver with sparse localization for tumor growth models S Subramanian, K Scheufele, M Mehl, G Biros Inverse problems 36 (4), 045006, 2020 | 42 | 2020 |
A plug-and-play coupling approach for parallel multi-field simulations HJ Bungartz, F Lindner, M Mehl, B Uekermann Computational Mechanics 55, 1119-1129, 2015 | 42 | 2015 |
Navier–Stokes and Lattice–Boltzmann on octree‐like grids in the Peano framework M Mehl, T Neckel, P Neumann International Journal for Numerical Methods in Fluids 65 (1‐3), 67-86, 2011 | 40 | 2011 |
Coupling brain-tumor biophysical models and diffeomorphic image registration K Scheufele, A Mang, A Gholami, C Davatzikos, G Biros, M Mehl Computer methods in applied mechanics and engineering 347, 533-567, 2019 | 39 | 2019 |