| Deep Potential Molecular Dynamics: a scalable model with the accuracy of quantum mechanics L Zhang, J Han, H Wang, R Car, W E arXiv preprint arXiv:1707.09571, 2017 | 359 | 2017 |
| Comparative atomistic and coarse-grained study of water: What do we lose by coarse-graining? H Wang, C Junghans, K Kremer The European Physical Journal E: Soft Matter and Biological Physics 28 (2 …, 2009 | 241 | 2009 |
| DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics H Wang, L Zhang, J Han, W E arXiv preprint arXiv:1712.03641, 2017 | 148 | 2017 |
| Active Learning of Uniformly Accurate Inter-atomic Potentials for Materials Simulation L Zhang, DY Lin, H Wang, R Car, W E arXiv preprint arXiv:1810.11890, 2018 | 125 | 2018 |
| Optimizing working parameters of the smooth particle mesh Ewald algorithm in terms of accuracy and efficiency H Wang, F Dommert, C Holm The Journal of chemical physics 133, 034117, 2010 | 98 | 2010 |
| Grand-canonical-like molecular-dynamics simulations by using an adaptive-resolution technique H Wang, C Hartmann, C Schütte, L Delle Site Physical Review X 3 (1), 011018, 2013 | 97 | 2013 |
| End-to-end Symmetry Preserving Inter-atomic Potential Energy Model for Finite and Extended Systems L Zhang, J Han, H Wang, WA Saidi, R Car, W E arXiv preprint arXiv:1805.09003, 2018 | 85 | 2018 |
| DeePCG: constructing coarse-grained models via deep neural networks L Zhang, J Han, H Wang, R Car, W E arXiv preprint arXiv:1802.08549, 2018 | 72 | 2018 |
| Adaptive resolution simulation (AdResS): A smooth thermodynamic and structural transition from atomistic to coarse grained resolution and vice versa in a grand canonical fashion H Wang, C Schütte, L Delle Site Journal of Chemical Theory and Computation 8 (8), 2878-2887, 2012 | 59 | 2012 |
| Chemical potential of liquids and mixtures via adaptive resolution simulation A Agarwal, H Wang, C Schütte, LD Site The Journal of chemical physics 141 (3), 034102, 2014 | 53 | 2014 |
| Applications of the cross-entropy method to importance sampling and optimal control of diffusions W Zhang, H Wang, C Hartmann, M Weber, C Schütte SIAM Journal on Scientific Computing 36 (6), A2654-A2672, 2014 | 52 | 2014 |
| Molecular dynamics in a grand ensemble: Bergmann–Lebowitz model and adaptive resolution simulation A Agarwal, J Zhu, C Hartmann, H Wang, L Delle Site New Journal of Physics 17 (8), 083042, 2015 | 51 | 2015 |
| DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models Y Zhang, H Wang, W Chen, J Zeng, L Zhang, H Wang, E Weinan Computer Physics Communications 253, 107206, 2020 | 36 | 2020 |
| Reinforced dynamics for enhanced sampling in large atomic and molecular systems L Zhang, H Wang, W E The Journal of Chemical Physics, 2018 | 31 | 2018 |
| Crucial properties of the moment closure model FENE-QE H Wang, K Li, P Zhang Journal of Non-Newtonian Fluid Mechanics 150 (2-3), 80-92, 2008 | 30 | 2008 |
| An efficient adaptive mesh redistribution method for a non-linear Dirac equation H Wang, H Tang Journal of Computational Physics 222 (1), 176-193, 2007 | 29 | 2007 |
| Building Markov State Models for Periodically Driven Non-Equilibrium Systems H Wang, C Schütte Journal of Chemical Theory and Computation 11 (4), 1819-1831, 2015 | 25 | 2015 |
| Determining hydrodynamic boundary conditions from equilibrium fluctuations S Chen, H Wang, T Qian, P Sheng Physical Review E 92 (4), 043007, 2015 | 24 | 2015 |
| Exploring the conformational dynamics of alanine dipeptide in solution subjected to an external electric field: A nonequilibrium molecular dynamics simulation H Wang, C Schütte, G Ciccotti, L Delle Site Journal of Chemical Theory and Computation 10 (4), 1376-1386, 2014 | 18 | 2014 |
| Error estimate of short-range force calculation in inhomogeneous molecular systems H Wang, C Schütte, P Zhang Physical Review E 86 (2), 026704, 2012 | 17 | 2012 |
Luigi Delle SiteInstitute for Mathematics, Department of Mathematics and Computer Science, Freie Universität Berlin確認したメール アドレス: fu-berlin.de
