KG embedding methods based on graph convolutional networks (GCNs) have recently gained significant attention due to their ability to add information of neighboring nodes into the nodes' embeddings. However, existing GCNs are primarily based on real-valued embeddings, which have high distortion, ...
In GCN, the feature aggregation at each node assumes that all neighbours have same importance which may reduce the model capacity. Graph attention network (GAT) [20] is an approach which showed that, by providing attention to neighbours which can be learned by end-to-end training, we may bu...
Firstly, DMCF-DDI applies two Graph Convolutional Network (GCN) encoders to learn molecular structure and topological features from fingerprint and knowledge graphs, respectively. Secondly, an asymmetric skip connection (ASC) uses distinct semantic-level features to construct the complex-valued drug pair...
Deep feature mining via the attention-based bidirectional long short term memory graph convolutional neural network for human motor imagery recognition. Front. Bioeng. Biotechnol. 9, 706229 (2022). Article PubMed PubMed Central Google Scholar Gao, J., Geng, X., Zhang, Y., Wang, R. & Sha...
The idea is that when f is single-valued, a Reeb graph shows a quotient topology of X with respect to f and mapper discretizes this Reeb graph using the sampled values of f on points x1, …, xn. Algorithmically, mapper consists of the steps: 1. Sort the values fi and split ...
extended CV-CNNs to the realm of graph neural networks (GNNs), proposing a novel complex-valued graph neural network (CV-GNN) for ISAR (inverse synthetic aperture radar) image classification [31]. Recently, in 2024, Zhou et al. integrated the strengths of complex-valued neural networks with...
With the guided module, the base module pays more attention to the separability characteristics of targets, which aids the network to recognize different targets efficiently. Since the base module is a complex-valued network and the sub-aperture image itself is also complex-valued, the structure ...
In order to define ‘successful’ attacks and recoverable attacks against a network, some basic concepts about algebraic graph theory are first introduced. A directed network ς=(ν,ε,G) of order N consists of a set of nodes ν={v1,v2,…,vN}, a set of edges ε⊆ν×ν, and an...
between synchronization dynamics, complex networks topology and spectral graph analysis. Key words: Synchronization, complex networks, spectral analysis PACS: 05.45.Xt, 89.75.Fb 1 Introduction In 1998 Watts and Strogatz presented a simple model of network’s structure that was the seed of the modern...
(1) resistance for forestalling impacts and protecting highly valued resources, (2) resilience for improving the capacity of ecosystems to return to desired conditions after disturbance (ability to bounce back), and (3) response for facilitating ecosystem transition to a stable alternative state ...