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 251–300 of 982 papers

TitleStatusHype
A Survey on Temporal Interaction Graph Representation Learning: Progress, Challenges, and Opportunities—0
Multi-Granular Attention based Heterogeneous Hypergraph Neural Network—0
GRAPE: Heterogeneous Graph Representation Learning for Genetic Perturbation with Coding and Non-Coding Biotype—0
Multimodal Graph Representation Learning for Robust Surgical Workflow Recognition with Adversarial Feature Disentanglement—0
ABG-NAS: Adaptive Bayesian Genetic Neural Architecture Search for Graph Representation LearningCode0
OmniSage: Large Scale, Multi-Entity Heterogeneous Graph Representation Learning—0
GT-SVQ: A Linear-Time Graph Transformer for Node Classification Using Spiking Vector QuantizationCode0
Multimodal Spatio-temporal Graph Learning for Alignment-free RGBT Video Object Detection—0
Local Distance-Preserving Node Embeddings and Their Performance on Random GraphsCode0
Leveraging Auto-Distillation and Generative Self-Supervised Learning in Residual Graph Transformers for Enhanced Recommender Systems—0
Inductive Graph Representation Learning with Quantum Graph Neural Networks—0
LGIN: Defining an Approximately Powerful Hyperbolic GNNCode0
Node Embeddings via Neighbor Embeddings—0
MSNGO: multi-species protein function annotation based on 3D protein structure and network propagationCode0
AugWard: Augmentation-Aware Representation Learning for Accurate Graph ClassificationCode0
Graph-Based Re-ranking: Emerging Techniques, Limitations, and Opportunities—0
Multi-View Node Pruning for Accurate Graph Representation—0
Fine-tuning Vision Language Models with Graph-based Knowledge for Explainable Medical Image Analysis—0
Diffusion Model Agnostic Social Influence Maximization in Hyperbolic Space—0
Democratizing Large Language Model-Based Graph Data Augmentation via Latent Knowledge GraphsCode0
Graph Neural Network-based Spectral Filtering Mechanism for Imbalance Classification in Network Digital Twin—0
DICE: Device-level Integrated Circuits Encoder with Graph Contrastive PretrainingCode0
Graph Contrastive Learning for Connectome ClassificationCode0
Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics—0
Leveraging Joint Predictive Embedding and Bayesian Inference in Graph Self Supervised LearningCode0
Spectro-Riemannian Graph Neural Networks—0
Contrastive Learning Meets Pseudo-label-assisted Mixup Augmentation: A Comprehensive Graph Representation Framework from Local to GlobalCode0
Mamba-Based Graph Convolutional Networks: Tackling Over-smoothing with Selective State Space—0
Deep Modularity Networks with Diversity--Preserving Regularization—0
Graph Representation Learning with Diffusion Generative Models—0
Community-Aware Temporal Walks: Parameter-Free Representation Learning on Continuous-Time Dynamic GraphsCode0
Optimizing Blockchain Analysis: Tackling Temporality and Scalability with an Incremental Approach with Metropolis-Hastings Random Walks—0
Benchmarking Graph Representations and Graph Neural Networks for Multivariate Time Series ClassificationCode0
CureGraph: Contrastive Multi-Modal Graph Representation Learning for Urban Living Circle Health Profiling and PredictionCode0
Optimizing Supply Chain Networks with the Power of Graph Neural Networks—0
KAN KAN Buff Signed Graph Neural Networks?—0
Data-Driven Self-Supervised Graph Representation LearningCode0
NoiseHGNN: Synthesized Similarity Graph-Based Neural Network For Noised Heterogeneous Graph Representation LearningCode0
LASE: Learned Adjacency Spectral EmbeddingsCode0
Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation LearningCode0
A Deep Probabilistic Framework for Continuous Time Dynamic Graph GenerationCode0
GNN-Transformer Cooperative Architecture for Trustworthy Graph Contrastive LearningCode0
Scam Detection for Ethereum Smart Contracts: Leveraging Graph Representation Learning for Secure Blockchain—0
A Comparative Study on Dynamic Graph Embedding based on Mamba and Transformers—0
Multi-Class and Multi-Task Strategies for Neural Directed Link PredictionCode0
RingFormer: A Ring-Enhanced Graph Transformer for Organic Solar Cell Property PredictionCode0
Bootstrapping Heterogeneous Graph Representation Learning via Large Language Models: A Generalized Approach—0
Mixture of Experts Meets Decoupled Message Passing: Towards General and Adaptive Node ClassificationCode0
Why Does Dropping Edges Usually Outperform Adding Edges in Graph Contrastive Learning?Code0
Fine-grained graph representation learning for heterogeneous mobile networks with attentive fusion and contrastive learning—0
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Benchmark Results

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