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In recent years, deep learning on graphs has achieved remarkable success in various domains.
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RCENR: A Reinforced and Contrastive Heterogeneous Network Reasoning Model for Explainable News Recommendation. In SIGIR . 1710–1720
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Deep single-cell RNA-seq data clustering with graph prototypical contrastive learning
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Certifiably Robust Graph Contrastive Learning
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RAHNet: Retrieval Augmented Hybrid Network for Long-tailed Graph Classification. In ACMMM . 3817–3826
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Graph Contrastive Learning for Multi-omics Data
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To Compress or Not to Compress–Self-Supervised Learning and Information Theory: A Review
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scGCC: Graph Contrastive Clustering with Neighborhood Augmentations for scRNA-seq Data Analysis
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Graph Contrastive Learning with Generative Adversarial Network. In KDD . 2721–2730
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Imgcl: Revisiting graph contrastive learning on imbalanced node classification. In AAAI , Vol. 37. 11138–11146
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A New Mechanism for Eliminating Implicit Conflict in Graph Contrastive Learning. In AAAI , Vol. 38. 12340–12348
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