SOTAVerified

Graph Representation Learning

The goal of Graph Representation Learning is to construct a set of features (‘embeddings’) representing the structure of the graph and the data thereon. We can distinguish among Node-wise embeddings, representing each node of the graph, Edge-wise embeddings, representing each edge in the graph, and Graph-wise embeddings representing the graph as a whole.

Source: SIGN: Scalable Inception Graph Neural Networks

Papers

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Showing 101–150 of 982 papers

TitleStatusHype
GRATIS: Deep Learning Graph Representation with Task-specific Topology and Multi-dimensional Edge FeaturesCode1
GripNet: Graph Information Propagation on Supergraph for Heterogeneous GraphsCode1
Heterogeneous Graph Representation Learning with Relation AwarenessCode1
AutoGCL: Automated Graph Contrastive Learning via Learnable View GeneratorsCode1
A Meta-Learning Approach for Graph Representation Learning in Multi-Task SettingsCode1
HGCLIP: Exploring Vision-Language Models with Graph Representations for Hierarchical UnderstandingCode1
Hierarchical Heterogeneous Graph Representation Learning for Short Text ClassificationCode1
Histopathology Whole Slide Image Analysis with Heterogeneous Graph Representation LearningCode1
Hybrid intelligence for dynamic job-shop scheduling with deep reinforcement learning and attention mechanismCode1
Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily DiscriminatingCode1
Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training TasksCode1
Bi-GCN: Binary Graph Convolutional NetworkCode1
An adaptive graph learning method for automated molecular interactions and properties predictionsCode1
Is Distance Matrix Enough for Geometric Deep Learning?Code1
KPGT: Knowledge-Guided Pre-training of Graph Transformer for Molecular Property PredictionCode1
LazyGNN: Large-Scale Graph Neural Networks via Lazy PropagationCode1
Boosting Graph Structure Learning with Dummy NodesCode1
Boost then Convolve: Gradient Boosting Meets Graph Neural NetworksCode1
Large-Scale Representation Learning on Graphs via BootstrappingCode1
Learning Long Range Dependencies on Graphs via Random WalksCode1
An Effective and Efficient Entity Alignment Decoding Algorithm via Third-Order Tensor IsomorphismCode1
LMSOC: An Approach for Socially Sensitive PretrainingCode1
Deep Graph Contrastive Representation LearningCode1
Machine Learning on Graphs: A Model and Comprehensive TaxonomyCode1
An Open Challenge for Inductive Link Prediction on Knowledge GraphsCode1
MAGNET: Multi-Label Text Classification using Attention-based Graph Neural NetworkCode1
DyTed: Disentangled Representation Learning for Discrete-time Dynamic GraphCode1
Unleashing the Power of Graph Data Augmentation on Covariate Distribution ShiftCode1
EchoGLAD: Hierarchical Graph Neural Networks for Left Ventricle Landmark Detection on EchocardiogramsCode1
Enhancing Graph Representation Learning with Localized Topological FeaturesCode1
Domain Adversarial Spatial-Temporal Network: A Transferable Framework for Short-term Traffic Forecasting across CitiesCode1
Does Invariant Graph Learning via Environment Augmentation Learn Invariance?Code1
Catastrophic Forgetting in Deep Graph Networks: an Introductory Benchmark for Graph ClassificationCode1
Distribution-Aware Graph Representation Learning for Transient Stability Assessment of Power SystemCode1
Does Graph Distillation See Like Vision Dataset Counterpart?Code1
DropMessage: Unifying Random Dropping for Graph Neural NetworksCode1
CCGL: Contrastive Cascade Graph LearningCode1
A Representation Learning Framework for Property GraphsCode1
Multi-hop Attention Graph Neural NetworkCode1
Edge Representation Learning with HypergraphsCode1
Certifiably Robust Graph Contrastive LearningCode1
Efficient and Feasible Robotic Assembly Sequence Planning via Graph Representation LearningCode1
Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand PredictionCode1
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic GraphsCode1
A Proposal of Multi-Layer Perceptron with Graph Gating Unit for Graph Representation Learning and its Application to Surrogate Model for FEMCode1
Disentangle-based Continual Graph Representation LearningCode1
Fast Graph Learning with Unique Optimal SolutionsCode1
Class-Imbalanced Learning on Graphs: A SurveyCode1
A step towards neural genome assemblyCode1
TransGNN: Harnessing the Collaborative Power of Transformers and Graph Neural Networks for Recommender SystemsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Pi-net-linearError (mm)0.47—Unverified