Graph Quantum Neural Tangent Kernel (GraphQNTK):这一模型基于图神经切核,利用无限宽度的量子图神经网络进行图分类任务。它是当前处理大规模图数据的主要量子图神经网络算法之一,但仍然面临量子设备规模有限的问题。 4. 核心思想 4.1 自我图分解处理策略 为了克服量子设备上量子比特数量的限制,作者提出了自我图分解策略...
图神经网络论文笔记4:Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective(PGD) Abner OOD / LLM / 3DV / 25Fall5 人赞同了该文章 这篇文章提出了一种针对节点分类的攻击,属于白盒无差别攻击。由于图的离散型,传统的(一阶)连续的优化方法不能直接应用于修改图上链接的攻击。为...
TensorFlow was originally developed by researchers and engineers working within the Machine Intelligence team at Google Brain to conduct research in machine learning and neural networks. However, the framework is versatile enough to be used in other areas as well. ...
The realization of various knowledge graphs is based on complex networks. Also, the management and operation of knowledge graphs mainly depend on the graph and complex network-related algorithms. Integrated with complex network technology, the knowledge graph can improve the efficiency of knowledge ...
4 Graphs-based deep learning models 4.1 Graph convolutional network Graph Convolution Networks (GCN) [5] is a semi-supervised learning approach for Graph-based data, e.g., document type in a citation network. The approach is based on the efficient usage of CNNs, which work directly on grap...
Most of graph-based methods usually exploit GCN model to process the graph data structures. The extracted features can be used to finish the final task. For example, Zhang et al. [201,24,195] propose a model which is consisted by three encoders for temporal relation, spatial relation, and...
(nm–μm), shape, orientation, and adjacency relation of the grains. Here, we develop a graph neural network1,2based machine learning model which enables an accurate prediction of the property of polycrystalline microstructures and quantifying the relative importance of each feature in each grain ...
graph learning to predict reaction outcomes. With the development of graph neural networks (GNNs), many GNN-based frameworks have emerged for retrosynthesis and have achieved notable improvements in performance. For example, Shi et al.17. presented the G2G framework, which utilizes relational graph ...
Information provides the energy of commerce and forms the foundation to direct an organization’s activities. The asset view also means that anyone who touches data or content cannot do so in isolation. “I am going to download data, tweak it because I know it is not exact, and then ...
The neural network has been widely applied in building energy systems as a soft controller technique to recognize, reproduce, and anticipate complicated nonlinear correlations between system input and output parameters. The neural network is a data-driven calculation tool based on many computational ...