AAAI 2023 accepted papers on Graph learning
173 of the 2,023 papers accepted at AAAI 2023 (8.6%) are on Graph learning, compared with 8.0% at AAAI 2022. They fall into 4 topics.
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Topics and papers
Knowledge and temporal graphs · 63 papers
- PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow Prediction (621 citations)
- Simple and Efficient Heterogeneous Graph Neural Network (224 citations)
- Temporal Knowledge Graph Reasoning with Historical Contrastive Learning (159 citations)
- Next POI Recommendation with Dynamic Graph and Explicit Dependency (70 citations)
- Scalable Spatiotemporal Graph Neural Networks (70 citations)
- SKIER: A Symbolic Knowledge Integrated Model for Conversational Emotion Recognition (70 citations)
- Joint Multimodal Entity-Relation Extraction Based on Edge-Enhanced Graph Alignment Network and Word-Pair Relation Tagging (67 citations)
- Spatio-Temporal Graph Neural Point Process for Traffic Congestion Event Prediction (64 citations)
- A Set of Control Points Conditioned Pedestrian Trajectory Prediction (58 citations)
- GRLSTM: Trajectory Similarity Computation with Graph-Based Residual LSTM (45 citations)
- T2G-FORMER: Organizing Tabular Features into Relation Graphs Promotes Heterogeneous Feature Interaction (42 citations)
- Unbiased Heterogeneous Scene Graph Generation with Relation-Aware Message Passing Neural Network (40 citations)
and 51 more in the interactive map.
Graph self-supervised learning · 52 papers
- Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View (134 citations)
- Cluster-Guided Contrastive Graph Clustering Network (132 citations)
- Neighbor Contrastive Learning on Learnable Graph Augmentation (121 citations)
- Semi-supervised Credit Card Fraud Detection via Attribute-Driven Graph Representation (121 citations)
- Heterogeneous Graph Masked Autoencoders (107 citations)
- Spectral Feature Augmentation for Graph Contrastive Learning and Beyond (84 citations)
- MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning (75 citations)
- Multi-Relational Contrastive Learning Graph Neural Network for Drug-Drug Interaction Event Prediction (67 citations)
- Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating (62 citations)
- Molformer: Motif-Based Transformer on 3D Heterogeneous Molecular Graphs (61 citations)
- Attribute and Structure Preserving Graph Contrastive Learning (55 citations)
- DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery – a Focus on Affinity Prediction Problems with Noise Annotations (48 citations)
and 40 more in the interactive map.
GNN architectures · 30 papers
- Federated Learning on Non-IID Graphs via Structural Knowledge Sharing (165 citations)
- DropMessage: Unifying Random Dropping for Graph Neural Networks (64 citations)
- Substructure Aware Graph Neural Networks (56 citations)
- T2-GNN: Graph Neural Networks for Graphs with Incomplete Features and Structure via Teacher-Student Distillation (49 citations)
- Let Graph Be the Go Board: Gradient-Free Node Injection Attack for Graph Neural Networks via Reinforcement Learning (39 citations)
- Graph Ordering Attention Networks (36 citations)
- GraphSR: A Data Augmentation Algorithm for Imbalanced Node Classification (36 citations)
- Boosting Graph Neural Networks via Adaptive Knowledge Distillation (31 citations)
- Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis (31 citations)
- On Generalized Degree Fairness in Graph Neural Networks (30 citations)
- Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting It into MLPs: An Effective GNN-to-MLP Distillation Framework (29 citations)
- Interpreting Unfairness in Graph Neural Networks via Training Node Attribution (24 citations)
and 18 more in the interactive map.
Graph algorithms and clustering · 28 papers
- Hard Sample Aware Network for Contrastive Deep Graph Clustering (128 citations)
- Let the Data Choose: Flexible and Diverse Anchor Graph Fusion for Scalable Multi-View Clustering (72 citations)
- Data Imputation with Iterative Graph Reconstruction (24 citations)
- Scalable Attributed-Graph Subspace Clustering (20 citations)
- Opinion Optimization in Directed Social Networks (19 citations)
- Priori Anchor Labels Supervised Scalable Multi-View Bipartite Graph Clustering (18 citations)
- AutoGraph: Optimizing DNN Computation Graph for Parallel GPU Kernel Execution (12 citations)
- Scalable Edge Blocking Algorithms for Defending Active Directory Style Attack Graphs (12 citations)
- Graphs, Constraints, and Search for the Abstraction and Reasoning Corpus (11 citations)
- GMDNet: A Graph-Based Mixture Density Network for Estimating Packages’ Multimodal Travel Time Distribution (10 citations)
- Grouping Matrix Based Graph Pooling with Adaptive Number of Clusters (8 citations)
- Can Graph Neural Networks Learn to Solve the MaxSAT Problem? (Student Abstract) (6 citations)
and 16 more in the interactive map.