Results 51 to 60 of about 415,143 (70)
Auto-HeG: Automated Graph Neural Network on Heterophilic Graphs
, 2023 Graph neural architecture search (NAS) has gained popularity in automatically designing powerful graph neural networks (GNNs) with relieving human efforts.
Chuan Zhou, Qin Zhang, Shirui Pan
exaly +3 more sources
The Heterophilic Snowflake Hypothesis: Training and Empowering GNNs for Heterophilic Graphs
Graph Neural Networks (GNNs) have become pivotal tools for a range of graph-based learning tasks. Notably, most current GNN architectures operate under the assumption of homophily, whether explicitly or implicitly.
Wei Huang, Guohao Li, Shirui Pan
exaly +3 more sources
MUSE: Multi-View Contrastive Learning for Heterophilic Graphs
, 2023 In recent years, self-supervised learning has emerged as a promising approach in addressing the issues of label dependency and poor generalization performance in traditional GNNs.
Minjie Chen, Mengyi Yuan
exaly +1 more source
Some of the next articles are maybe not open access.
Related searches:
Related searches:
Taming over-smoothing representation on heterophilic graphs
Information Sciences, 2023Kai Guo, Zhining Liu, Yi Chang
exaly
Improving the Homophily of Heterophilic Graphs for Semi-Supervised Node Classification
2023Shiming Xiang
exaly
Heterophilic antibody interference in immunometric assays
Best Practice & Research Clinical Endocrinology & Metabolism, 2013Kjell Nustad
exaly
CAT: A causal graph attention network for trimming heterophilic graphs
Information SciencesXinsha FU, Ronghua Du, Haifeng Li
exaly
Graph Aggregating-Repelling Network: Do Not Trust All Neighbors in Heterophilic Graphs
Neural NetworksShiming Xiang +2 more
exaly
Make Heterophilic Graphs Better Fit GNN: A Graph Rewiring Approach
IEEE Transactions on Knowledge and Data EngineeringYanlin Wang, Shi Han, Lun Du
exaly