mlsanityData to 14 Oct 2026

Multi-view Graph Contrastive Representation Learning for Drug-Drug Interaction Prediction

arXiv 2010.11711 ↗First posted 22 Oct 2020cs.LG cs.AIcited by 41

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Abstract (arXiv)

Drug-drug interaction(DDI) prediction is an important task in the medical health machine learning community. This study presents a new method, multi-view graph contrastive representation learning for drug-drug interaction prediction, MIRACLE for brevity, to capture inter-view molecule structure and intra-view interactions between molecules simultaneously. MIRACLE treats a DDI network as a multi-view graph where each node in the interaction graph itself is a drug molecular graph instance. We use GCNs and bond-aware attentive message passing networks to encode DDI relationships and drug molecular graphs in the MIRACLE learning stage, respectively. Also, we propose a novel unsupervised contrastive learning component to balance and integrate the multi-view information. Comprehensive experiments on multiple real datasets show that MIRACLE outperforms the state-of-the-art DDI prediction models consistently.

Key facts. Cited by 41 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 Oct 2020.

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Citing papers per year: 2021: 4; 2022: 15; 2023: 8; 2024: 6; 2025: 6; 2026: 2.

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  1. 2021Graph Self-Supervised Learning: A Surveycited by 289
  2. 2021Pre-training Molecular Graph Representation with 3D Geometrycited by 248
  3. 2022Towards Unsupervised Deep Graph Structure Learningcited by 114
  4. 2022Graph Data Augmentation for Graph Machine Learning: A Surveycited by 62
  5. 2022Let Invariant Rationale Discovery Inspire Graph Contrastive Learningcited by 57
  6. 2022Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminatingcited by 57
  7. 2022GOOD-D: On Unsupervised Graph Out-Of-Distribution Detectioncited by 47
  8. 2023Conditional Graph Information Bottleneck for Molecular Relational Learningcited by 24
  9. 2022Dual Space Graph Contrastive Learningcited by 20
  10. 2022Semi-Supervised Hierarchical Graph Classificationcited by 15
  11. 2023Shift-Robust Molecular Relational Learning with Causal Substructurecited by 15
  12. 2022Multi-task Joint Strategies of Self-supervised Representation Learning on Biomedical Networks for Drug Discoverycited by 13
29 more
  1. 2022From Unsupervised to Few-shot Graph Anomaly Detection: A Multi-scale Contrastive Learning Approachcited by 13
  2. 2022Contrastive Knowledge Graph Error Detectioncited by 11
  3. 2024Noise-Resilient Unsupervised Graph Representation Learning via Multi-Hop Feature Quality Estimationcited by 11
  4. 2023Comprehensive evaluation of deep and graph learning on drug-drug interactions predictioncited by 10
  5. 2024Can Large Language Models Understand Molecules?cited by 10
  6. 2021A Unified View of Relational Deep Learning for Drug Pair Scoringcited by 7
  7. 2022Hierarchical Graph Representation Learning for the Prediction of Drug-Target Binding Affinitycited by 7
  8. 2024Graph Contrastive Learning with Cohesive Subgraph Awarenesscited by 6
  9. 2025LLMs for Drug-Drug Interaction Prediction: A Comprehensive Comparisoncited by 5
  10. 2023Signed Directed Graph Contrastive Learning with Laplacian Augmentationcited by 4
  11. 2022Knowledge-informed Molecular Learning: A Survey on Paradigm Transfercited by 3
  12. 2022Graph neural networks and attention-based CNN-LSTM for protein classificationcited by 3
  13. 2025Representational Alignment with Chemical Induced Fit for Molecular Relational Learningcited by 2
  14. 2025HiGraph: A Large-Scale Hierarchical Graph Dataset for Malware Analysiscited by 2
  15. 2026OpenDDI: A Comprehensive Benchmark for DDI Predictioncited by 2
  16. 2022Self-supervised Learning for Heterogeneous Graph via Structure Information based on Metapathcited by 1
  17. 2023Contrastive Learning-based Imputation-Prediction Networks for In-hospital Mortality Risk Modeling using EHRscited by 1
  18. 2023MotifPiece: A Data-Driven Approach for Effective Motif Extraction and Molecular Representation Learningcited by 1
  19. 2024Long-context Protein Language Modeling Using Bidirectional Mamba with Shared Projection Layerscited by 1
  20. 2025Khan-GCL: Kolmogorov-Arnold Network Based Graph Contrastive Learning with Hard Negativescited by 1
  21. 2021AKE-GNN: Effective Graph Learning with Adaptive Knowledge Exchangecited by 0
  22. 2022Multi-View Substructure Learning for Drug-Drug Interaction Predictioncited by 0
  23. 2023Subgraph Networks Based Contrastive Learningcited by 0
  24. 2023Curvature-enhanced Graph Convolutional Network for Biomolecular Interaction Predictioncited by 0
  25. 2024How to Bridge Spatial and Temporal Heterogeneity in Link Prediction? A Contrastive Methodcited by 0
  26. 20243D Interaction Geometric Pre-training for Molecular Relational Learningcited by 0
  27. 2025MolBridge: Atom-Level Joint Graph Refinement for Robust Drug-Drug Interaction Event Predictioncited by 0
  28. 2025Hypergraph Contrastive Learning for both Homophilic and Heterophilic Hypergraphscited by 0
  29. 2026Cross-Domain Molecular Relational Learning: Leveraging Chemical Structure-Activity Analysiscited by 0