文章指出WL-test 是 GNN 的性能上界,通篇文章都在使GNN能够接近WL算法 一般来说,一个好的 GNN 的算法仅仅会在两个节点具有相同子树结构的情况下才会将其映射到同一位置。由于子树结构是通过节点邻域递归定义的,所以我们可以将分析简化为这样一个问题:GNN 是否会映射两个邻域到相同的 Representation?一个好的 GNN ...
Keywords:GNN, Heterophily, Homophily, Node Classification https://arxiv.org/pdf/2306.13532.pdfarxiv.org/pdf/2306.13532.pdf Case 图上的高阶相似性如下图所示,这促使我们利用高阶信息来缓解异质性问题。 Introduction 本文贡献如下: 本文首次提出了一种基于特征相似性的路径采样策略来获得高阶信息,以缓...
Deep learning models have shown promise in diagnosing neurodevelopmental disorders (NDD) like ASD and ADHD. However, many models either use graph neural networks (GNN) to construct single-level brain functional networks (BFNs) or employ spatial convolution filtering for local information extraction ...
Graph neural networks (GNN) have been proven to be mature enough for handling graph-structured data on node-level graph representation learning tasks. However, the graph pooling technique for learning expressive graph-level representation is critical yet still challenging. Existing pooling methods either...
However, not all GNN models outperform simple heuristic algorithms in link prediction tasks. Most traditional GNNs have limitations in their expressive power when dealing with link prediction tasks, and they might lack the capability to effectively grasp complex structural features in the graph, such ...
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python src/train_gnn.py To run hyperparameter optimization, execute: python src/optimize_hps_gnn.py Illustrative notebook: src/gnn_homm_nb.ipynb Default configuration file for train_gnn.py: src/configs/train_gnn.yml Default configuration file for optimize_hps_gnn.py: src/configs/hp_opt_gnn...
a GNN-based predictor and a reasoning path distiller. The reasoning path distiller explores high-order graph structures such as reasoning paths and encodes them as rich-semantic edges, explicitly compositing long-range dependencies into the predictor. This step also plays an essential role in densifyi...
Therefore, we propose a novel high-order attentive graph neural network (HA-GNN) model for session-based recommendations. In the proposed method, first, we model sessions as graph-structured data. Then, we use the self-attention mechanism to capture the dependencies between items. Next, we use...
In recent research, supervised image clustering based on Graph Neural Networks (GNN) connectivity prediction has demonstrated considerable improvements ove... Q Zhao,L Li,Y Chu,... - 《Remote Sensing》 被引量: 0发表: 2022年 Density Division Face Clustering Based on Graph Convolutional Networks Su...