GAPointNet: graph attention based point neural network for exploiting local feature of point cloud. Neurocomputing 438, 122–132 (2021). Article Google Scholar Fenton, M. J. et al. Permutationless many-jet event reconstruction with symmetry preserving attention networks. Phys. Rev. D 105, ...
Fig. 1: Laying out networks using neural network. a FDL optimizes the d dimensional node positions to find a network layout. b NodeMLP replaces the d dimensional input by a neural network that relies on a fully connected layer (FC) to project the high dimensional embedding to the d dimen...
[23] T. Kawamoto, M. Tsubaki, and T. Obuchi, “Mean-field theory of graph neural networks in graph partitioning,” in NeurIPS 2018, 2018, pp. 4366–4376. [24] F. Scarselli, M. Gori, A. C. Tsoi, M. Hagenbuchner, and G. Monfardini, “The graph neural network model,” IEEE TN...
(GGNN) have demonstrated ground-breaking performance on many tasks mentioned above. In this survey, we provide a detailed review over existing graph neural network models, systematically categorize the applications, and propose four open problems for future research.大量的学习任务需要处理包含丰富元素间...
Capsule Graph Neural Network. Zhang Xinyi, Lihui Chen. ICLR 2019. paper Can GCNs Go as Deep as CNNs?. Guohao Li, Matthias Müller, Ali Thabet, Bernard Ghanem. 2019. paper Heterogeneous Graph Attention Network. Xiao Wang, Houye Ji, Chuan Shi, Bai Wang, Peng Cui, P. Yu, Yanfang Ye...
Bai, Y., Ding, H., Bian, S., Chen, T., Sun, Y., Wang, W.: SimGNN: a neural network approach to fast graph similarity computation. In: Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, pp. 384–392 (2019) Google Scholar Bai, Y., Ding, H...
(GGNN) have demonstrated ground-breaking performance on many tasks mentioned above. In this survey, we provide a detailed review over existing graph neural network models, systematically categorize the applications, and propose four open problems for future research.大量的学习任务需要处理包含丰富元素间...
Graph Neural Networks 通过上面的描述，graph可以通过置换不变的邻接表表示，那么可以设计一个graph neura...
Physnet: a neural network for predicting energies, forces, dipole moments, and partial charges. J. Chem. Theory Comput. 15, 3678–3693 (2019). Article CAS Google Scholar Schmidt, J., Pettersson, L., Verdozzi, C., Botti, S. & Marques, M. A. L. Crystal graph attention networks for...
Graph theory is a very broad branch of mathematics that is applicable to real world problems. Compared with the dimensional disaster [15] caused by the increase of the block code length of the DL-based decoding algorithm, GNN [16,17,18] is an extension of existing neural network methods ...