Home ›
Entities
› academia
› Addressing imbalance in graph datasets: Introducing GATE-GNN with graph ensemble weight attention and transfer learning for enhanced node classification
Addressing imbalance in graph datasets: Introducing GATE-GNN with graph ensemble weight attention and transfer learning for enhanced node classification
Research article (Expert Systems with Applications, 2024) · cited 27× · AI/ML
Addressing imbalance in graph datasets: Introducing GATE-GNN with graph ensemble weight attention and transfer learning for enhanced node classification
Summary
Addressing imbalance in graph datasets: Introducing GATE-GNN with graph ensemble weight attention and transfer learning for enhanced node classification is a scholarly article[1].
Key Facts
Addressing imbalance in graph datasets: Introducing GATE-GNN with graph ensemble weight attention and transfer learning for enhanced node classification's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Addressing imbalance in graph datasets: Introducing GATE-GNN with graph ensemble weight attention and transfer learning for enhanced node classification. Retrieved May 24, 2026, from https://4ort.xyz/entity/addressing-imbalance-in-graph-datasets-introducing-gate-gnn-with-graph-ensemble-weight-attention-and-transfer-learning-f
MLA“Addressing imbalance in graph datasets: Introducing GATE-GNN with graph ensemble weight attention and transfer learning for enhanced node classification.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/addressing-imbalance-in-graph-datasets-introducing-gate-gnn-with-graph-ensemble-weight-attention-and-transfer-learning-f.
BibTeX@misc{4ortxyz_addressing-imbalance-in-graph-datasets-introducing-gate-gnn-with-graph-ensemble-weight-attention-and-transfer-learning-f_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Addressing imbalance in graph datasets: Introducing GATE-GNN with graph ensemble weight attention and transfer learning for enhanced node classification}}, year = {2026}, url = {https://4ort.xyz/entity/addressing-imbalance-in-graph-datasets-introducing-gate-gnn-with-graph-ensemble-weight-attention-and-transfer-learning-f}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Addressing imbalance in graph datasets: Introducing GATE-GNN with graph ensemble weight attention and transfer learning for enhanced node classification — https://4ort.xyz/entity/addressing-imbalance-in-graph-datasets-introducing-gate-gnn-with-graph-ensemble-weight-attention-and-transfer-learning-f (retrieved 2026-05-24)
