SOTAVerified

Graph Learning

Graph learning is a branch of machine learning that focuses on the analysis and interpretation of data represented in graph form. In this context, a graph is a collection of nodes (or vertices) and edges, where nodes represent entities and edges represent the relationships or interactions between these entities. This structure is particularly useful for modeling complex networks found in various domains such as social networks, biological networks, and communication networks.

Graph learning leverages the relationships and structures within the graph to learn and make predictions. It includes techniques like graph neural networks (GNNs), which extend the concept of neural networks to handle graph-structured data. These models are adept at capturing the dependencies and influence of connected nodes, leading to more accurate predictions in scenarios where relationships play a key role.

Key applications of graph learning include recommender systems, drug discovery, social network analysis, and fraud detection. By utilizing the inherent structure of graph data, graph learning algorithms can uncover deep insights and patterns that are not apparent with traditional machine learning approaches.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–250 of 1570 papers

TitleStatusHype
Data Augmentation for Deep Graph Learning: A SurveyCode1
Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why?Code1
CrossCBR: Cross-view Contrastive Learning for Bundle RecommendationCode1
Leveraging Large Language Models for Node Generation in Few-Shot Learning on Text-Attributed GraphsCode1
CaseLink: Inductive Graph Learning for Legal Case RetrievalCode1
CaT: Balanced Continual Graph Learning with Graph CondensationCode1
Covariant Compositional Networks For Learning GraphsCode1
Adversarial Bipartite Graph Learning for Video Domain AdaptationCode1
Appearance and Structure Aware Robust Deep Visual Graph Matching: Attack, Defense and BeyondCode1
Euler: Detecting Network Lateral Movement via Scalable Temporal Link PredictionCode1
Approximate Network Motif Mining Via Graph LearningCode1
3D Infomax improves GNNs for Molecular Property PredictionCode1
A Practical, Progressively-Expressive GNNCode1
CCGL: Contrastive Cascade Graph LearningCode1
Evaluating and Improving Graph-based Explanation Methods for Multi-Agent CoordinationCode1
Exphormer: Sparse Transformers for GraphsCode1
Geodesic Graph Neural Network for Efficient Graph Representation LearningCode1
Correlation-aware Spatial-Temporal Graph Learning for Multivariate Time-series Anomaly DetectionCode1
Examining the Effects of Degree Distribution and Homophily in Graph Learning ModelsCode1
CKGConv: General Graph Convolution with Continuous KernelsCode1
CktGNN: Circuit Graph Neural Network for Electronic Design AutomationCode1
Generative 3D Part Assembly via Dynamic Graph LearningCode1
State of the Art and Potentialities of Graph-level LearningCode1
Exploring Graph Tasks with Pure LLMs: A Comprehensive Benchmark and InvestigationCode1
Cluster-wise Graph Transformer with Dual-granularity Kernelized AttentionCode1
Fast Graph Learning with Unique Optimal SolutionsCode1
Fast and Distributed Equivariant Graph Neural Networks by Virtual Node LearningCode1
Learning Graph Quantized TokenizersCode1
Generative Causal Explanations for Graph Neural NetworksCode1
Learning on Attribute-Missing GraphsCode1
Convolutional Neural Networks on Graphs with Chebyshev Approximation, RevisitedCode1
A Fair Comparison of Graph Neural Networks for Graph ClassificationCode1
Learning from Counterfactual Links for Link PredictionCode1
GeneAnnotator: A Semi-automatic Annotation Tool for Visual Scene GraphCode1
Federated Learning on Non-IID Graphs via Structural Knowledge SharingCode1
Company-as-Tribe: Company Financial Risk Assessment on Tribe-Style Graph with Hierarchical Graph Neural NetworksCode1
Comprehensive evaluation of deep and graph learning on drug-drug interactions predictionCode1
A Simple Graph Contrastive Learning Framework for Short Text ClassificationCode1
Generative Contrastive Graph Learning for RecommendationCode1
GIPA: A General Information Propagation Algorithm for Graph LearningCode1
Confidence-Based Feature Imputation for Graphs with Partially Known FeaturesCode1
FedSSP: Federated Graph Learning with Spectral Knowledge and Personalized PreferenceCode1
Association Graph Learning for Multi-Task Classification with Category ShiftsCode1
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural NetworksCode1
Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsCode1
Long Range Graph BenchmarkCode1
Forward Learning of Graph Neural NetworksCode1
Fragmented Layer Grouping in GUI Designs Through Graph Learning Based on Multimodal InformationCode1
Neural graphical modelling in continuous-time: consistency guarantees and algorithmsCode1
Continuity Preserving Online CenterLine Graph LearningCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HaloGraphNetR^20.97—Unverified