They are of particular relevance for chemistry and materials science, as they directly work on a graph or structural representation of molecules and materials and therefore have full access to all relevant information required to characterize materials. In this Review, we provide an overview of the ...
The computation of the optimal layout is based on the observation that the necessary conditions for a local minimum are that \({\textstyle{{\partial E} \over {\partial x_m}}}\) = \({\textstyle{{\partial E} \over {\partial y_m}}}\) = 0 for 1 ≤ m ≤ n....
For undirected graphs, there can be at most one edge connected to the same two nodes. Subsequent edge statements using the same two nodes will identify the edge with the previously defined one and apply any attributes given in the edge statement....
The graph convolutional network (GCN) is a go-to solution for machine learning on graphs, but its training is notoriously difficult to scale both in terms
Additionally, we introduce a spatially balanced mean squared error (SBMSE) loss function to address the imbalanced distribution and spatial variability of meteorological variables. The CGNN is capable of extracting essential spatial features and aggregating them from a global perspective, thereby improving...
首先对于两个定义在同一个点集V上的图G_1,G_2，直观的看，如果我们从V中找任意两个子集U,W，这...
Note that the GBN topology has never been seen during the training phase for any one of the models. Table 1 shows the results for the three topologies. In this particular case, we show the Mean Absolute Percentage Error (MAPE), the Mean Squared Error (MSE), the Mean Absolute Error (MAE...
SA:直接在input处构建squared value反应特征重要性,直接处理bp过程。缺陷在于SA仅反应了输入和输出的敏感性但重要性的准确性欠佳,其次,模型存在过饱和问题。 Guided BP:与SA相似,但仅处理正项的梯度而忽略负的。缺陷与SA相同 CAM:将最后一层节点特征映射至输入空间寻找重要信息。这种方法要求GNN需要兼顾全局信息并且最...
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For classification tasks, we utilize the binary cross-entropy (BCE) loss combined with the sigmoid layer (BCEWithLogits loss) when training the graph encoder and the property prediction network, while for regression tasks, we apply the mean squared error loss. The Adam optimizer is applied to ...