MeshGraphNets的出现将促进研究学者们对于结构网格和非结构网格的流场快速预测提出更优和更新的网络架构,为进一步降低累积误差、提升泛化性奠定了良好的基础。 参考文献 [1] Pfaff T, Fortunato M, Sanchez-Gonzalez A, et al. Learning mesh-based simulation with graph networks[J]. arXiv preprint arXiv:2010.03...
Mesh-based simulations are central to modeling complex physical systems in many disciplines across science and engineering. Mesh representations support powerful numerical integration methods and their resolution can be adapted to strike favorable trade-offs between accuracy and efficiency. However, high-...
Learning Mesh-Based Simulation with Graph NetworksTobias PfaffMeire FortunatoAlvaro Sanchez-GonzalezPeter BattagliaInternational Conference on Learning Representations
Learning Mesh-Based Simulation with Graph Networks - Tobias Pfaff (DeepMind) 01:04:08 How DeepMind learns physics simulators with Graph Networks (w author interview) 35:34 Learning Mesh Based Simulation with Graph Networks Best Paper Award ICLR 2 10:31 How DeepMind learns physics simulators ...
Learning mesh-based simulation with graph networks. In International Conference on Learning Representations Vol. 8 (2020). Liu, Q. et al. OctSurf: efficient hierarchical voxel-based molecular surface representation for protein-ligand affinity prediction. J. Molec. Graph. Model. 105, 107865 (2021)...
"Learning mesh-based simulation with graph networks." arXiv preprint arXiv:2010.03409 (2020). ^Belbute-Peres, Filipe De Avila, Thomas Economon, and Zico Kolter. "Combining differentiable PDE solvers and graph neural networks for fluid flow prediction." international conference on machine learning....
Learning mesh-based simulation with graph networks. In International Conference on Learning Representations 2837 (ICLR, 2021). Schanz, D., Gesemann, S. & Schröder, A. Shake-The-Box: Lagrangian particle tracking at high particle image densities. Exp. Fluids 57, 70 (2016). Article Google ...
However, when the dimension of the problem becomes large, this mesh-based approach fails dramatically due to the curse of dimensionality because the mesh spacing of the grid must be small enough to capture the smallest feature size of the solution. So, to achieve 10× higher resolution of an...
A Deep Learning-Based Salient Feature-Preserving Algorithm for Mesh Simplification CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2865-2888, 2025, DOI:10.32604/cmc.2025.060260 - 16 April 2025 (This article belongs to the Special Issue: Computer Vision and Image Processing: Feature ...
Learning mesh-based simulation with graph networks. In International Conference on Learning Representations 4521–4622 (ICLR, 2020). Han, X., Gao, H., Pfaff, T., Wang, J. X. & Liu, L. Predicting physics in mesh-reduced space with temporal attention. In International Conference on Learning...