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Graph Neural Networks for Tabular Data Learning: A Survey with Taxonomy and Directions

https://doi.org/10.1145/3744918
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Fraud analytics using descriptive, predictive, and social network techniques a guide to data science for fraud detection
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Modeling Relational Data with Graph Convolutional Networks
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Sparse attention is all you need for pre-training on tabular data
inferredcites →https://doi.org/10.1016/j.aiopen.2021.01.001openalex-snapshot
Graph neural networks: A review of methods and applications
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Incremental and dynamic graph construction with application to image classification
inferredcites →https://doi.org/10.1016/j.ins.2022.06.039openalex-snapshot
Graph autoencoder-based unsupervised outlier detection
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A novel graph-based feature interaction model for click-through rate prediction
inferredcites →https://doi.org/10.1016/j.ipm.2022.103137openalex-snapshot
Causality-based CTR prediction using graph neural networks
inferredcites →https://doi.org/10.1016/j.jbi.2022.104027openalex-snapshot
Structure-aware siamese graph neural networks for encounter-level patient similarity learning
inferredcites →https://doi.org/10.1016/j.neunet.2020.06.005openalex-snapshot
Missing data imputation with adversarially-trained graph convolutional networks
inferredcites →https://doi.org/10.1016/j.neunet.2024.106180openalex-snapshot
Graph Neural Network contextual embedding for Deep Learning on tabular data
inferredcites →https://doi.org/10.1016/j.patcog.2021.108218openalex-snapshot
Financial time series forecasting with multi-modality graph neural network
inferredcites →https://doi.org/10.1038/s41586-020-2188-xopenalex-snapshot
A reference map of the human binary protein interactome
inferredcites →https://doi.org/10.1038/s41586-024-08328-6openalex-snapshot
Accurate predictions on small data with a tabular foundation model
inferredcites →https://doi.org/10.1038/s41598-023-32369-yopenalex-snapshot
A graph neural network-based bearing fault detection method
inferredcites →https://doi.org/10.1109/access.2020.3007835openalex-snapshot
GATE: Graph-Attention Augmented Temporal Neural Network for Medication Recommendation
inferredcites →https://doi.org/10.1109/access.2021.3116705openalex-snapshot
GCN-Int: A Click-Through Rate Prediction Model Based on Graph Convolutional Network Interaction
inferredcites →https://doi.org/10.1109/icdm.2010.127openalex-snapshot
Factorization Machines
inferredcites →https://doi.org/10.1109/jbhi.2020.3004143openalex-snapshot
Disease Prediction via Graph Neural Networks
inferredcites →https://doi.org/10.1109/tai.2022.3194869openalex-snapshot
Graph Representation Learning Meets Computer Vision: A Survey
inferredcites →https://doi.org/10.1109/tcbb.2021.3083566openalex-snapshot
Predicting the Survival of Cancer Patients With Multimodal Graph Neural Network
inferredcites →https://doi.org/10.1109/tim.2022.3181894openalex-snapshot
Self-Adaptation Graph Attention Network via Meta-Learning for Machinery Fault Diagnosis With Few Labeled Data
inferredcites →https://doi.org/10.1109/tkde.2020.2981333openalex-snapshot
Deep Learning on Graphs: A Survey
inferredcites →https://doi.org/10.1109/tkde.2020.3008732openalex-snapshot
A Graph Neural Network Framework for Social Recommendations
inferredcites →https://doi.org/10.1109/tkde.2021.3077524openalex-snapshot
Cross-GCN: Enhancing Graph Convolutional Network with k-Order Feature Interactions
inferredcites →https://doi.org/10.1109/tkde.2021.3112749openalex-snapshot
Lifelong Property Price Prediction: A Case Study for the Toronto Real Estate Market
inferredcites →https://doi.org/10.1109/tkde.2021.3118815openalex-snapshot
A Comprehensive Survey on Graph Anomaly Detection With Deep Learning
inferredcites →https://doi.org/10.1109/tkde.2022.3145690openalex-snapshot
A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendation
inferredcites →https://doi.org/10.1109/tkde.2022.3172903openalex-snapshot
Graph Self-Supervised Learning: A Survey
inferredcites →https://doi.org/10.1109/tkde.2022.3198689openalex-snapshot
Graph Neural Networks for Missing Value Classification in a Task-driven Metric Space
inferredcites →https://doi.org/10.1109/tkde.2023.3249186openalex-snapshot
Deep Tabular Data Modeling With Dual-Route Structure-Adaptive Graph Networks
inferredcites →https://doi.org/10.1109/tkde.2024.3440654openalex-snapshot
Cross-Feature Interactive Tabular Data Modeling With Multiplex Graph Neural Networks
inferredcites →https://doi.org/10.1109/tnnls.2019.2917696openalex-snapshot
Learning Low-Dimensional Latent Graph Structures: A Density Estimation Approach
inferredcites →https://doi.org/10.1109/tnnls.2020.2978386openalex-snapshot
A Comprehensive Survey on Graph Neural Networks
inferredcites →https://doi.org/10.1109/tnnls.2021.3132376openalex-snapshot
Interaction-Aware Graph Neural Networks for Fault Diagnosis of Complex Industrial Processes
inferredcites →https://doi.org/10.1109/tnnls.2021.3133262openalex-snapshot
Graph-Based Class-Imbalance Learning With Label Enhancement
inferredcites →https://doi.org/10.1109/tnnls.2022.3190420openalex-snapshot
Deep Unsupervised Active Learning on Learnable Graphs
inferredcites →https://doi.org/10.1109/tnnls.2022.3229161openalex-snapshot
Deep Neural Networks and Tabular Data: A Survey
inferredcites →https://doi.org/10.1109/tnnls.2023.3257325openalex-snapshot
Homophily-Enhanced Self-Supervision for Graph Structure Learning: Insights and Directions
inferredcites →https://doi.org/10.1109/tnnls.2024.3488087openalex-snapshot
Adaptive Graph Convolutional Network for Unsupervised Generalizable Tabular Representation Learning
inferredcites →https://doi.org/10.1109/tpami.2021.3066111openalex-snapshot
Graph Regularized Autoencoder and its Application in Unsupervised Anomaly Detection
inferredcites →https://doi.org/10.1109/tpami.2022.3170249openalex-snapshot
Differentiable Graph Module (DGM) for Graph Convolutional Networks
inferredcites →https://doi.org/10.1109/tpami.2022.3182052openalex-snapshot
HGNN + : General Hypergraph Neural Networks
inferredcites →https://doi.org/10.1109/tpami.2024.3443141openalex-snapshot
A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection
inferredcites →https://doi.org/10.1109/tsp.2007.896065openalex-snapshot
Correntropy: Properties and Applications in Non-Gaussian Signal Processing
inferredcites →https://doi.org/10.1137/1.9781611977172openalex-snapshot
Proceedings of the 2022 SIAM International Conference on Data Mining (SDM)
inferredcites →https://doi.org/10.1145/1183614openalex-snapshot
Proceedings of the 15th ACM international conference on Information and knowledge management - CIKM '06
inferredcites →https://doi.org/10.1145/1273496openalex-snapshot
Proceedings of the 24th international conference on Machine learning
inferredcites →https://doi.org/10.1145/2783258.2783309openalex-snapshot
Dimensionality Reduction Via Graph Structure Learning
inferredcites →https://doi.org/10.1145/2988450.2988454openalex-snapshot
Wide & Deep Learning for Recommender Systems
inferredcites →https://doi.org/10.1145/3200765openalex-snapshot
Visual Analytics of Heterogeneous Data Using Hypergraph Learning
inferredcites →https://doi.org/10.1145/3219819.3220023openalex-snapshot
xDeepFM
inferredcites →https://doi.org/10.1145/3309547openalex-snapshot
Temporal Relational Ranking for Stock Prediction
inferredcites →https://doi.org/10.1145/3340531.3411903openalex-snapshot
Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters
inferredcites →https://doi.org/10.1145/3340531.3412724openalex-snapshot
Loan Default Analysis with Multiplex Graph Learning
inferredcites →https://doi.org/10.1145/3366423.3380027openalex-snapshot
Heterogeneous Graph Transformer
inferredcites →https://doi.org/10.1145/3394486.3403049openalex-snapshot
Graph Structure Learning for Robust Graph Neural Networks
inferredcites →https://doi.org/10.1145/3397191openalex-snapshot
On Proximity and Structural Role-based Embeddings in Networks
inferredcites →https://doi.org/10.1145/3404835.3462879openalex-snapshot
Learning Graph Meta Embeddings for Cold-Start Ads in Click-Through Rate Prediction
inferredcites →https://doi.org/10.1145/3408889openalex-snapshot
Fast Distributed k NN Graph Construction Using Auto-tuned Locality-sensitive Hashing
inferredcites →https://doi.org/10.1145/3442381.3449957openalex-snapshot
RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation
inferredcites →https://doi.org/10.1145/3442381.3449989openalex-snapshot
Pick and Choose: A GNN-based Imbalanced Learning Approach for Fraud Detection
inferredcites →https://doi.org/10.1145/3447548.3467066openalex-snapshot
FIVES: Feature Interaction Via Edge Search for Large-Scale Tabular Data
inferredcites →https://doi.org/10.1145/3447548.3467115openalex-snapshot
Incorporating Prior Financial Domain Knowledge into Neural Networks for Implied Volatility Surface Prediction
inferredcites →https://doi.org/10.1145/3447548.3467142openalex-snapshot
Intention-aware Heterogeneous Graph Attention Networks for Fraud Transactions Detection
inferredcites →https://doi.org/10.1145/3447548.3467216openalex-snapshot
Retrieval & Interaction Machine for Tabular Data Prediction
inferredcites →https://doi.org/10.1145/3447548.3467384openalex-snapshot
Dual Graph enhanced Embedding Neural Network for CTR Prediction
inferredcites →https://doi.org/10.1145/3459637.3481912openalex-snapshot
Efficient Learning to Learn a Robust CTR Model for Web-scale Online Sponsored Search Advertising
inferredcites →https://doi.org/10.1145/3459637.3482277openalex-snapshot
Modeling Heterogeneous Graph Network on Fraud Detection
inferredcites →https://doi.org/10.1145/3485447.3512178openalex-snapshot
AUC-oriented Graph Neural Network for Fraud Detection
inferredcites →https://doi.org/10.1145/3485447.3512186openalex-snapshot
Towards Unsupervised Deep Graph Structure Learning
inferredcites →https://doi.org/10.1145/3485447.3512195openalex-snapshot
H2-FDetector: A GNN-based Fraud Detector with Homophilic and Heterophilic Connections
inferredcites →https://doi.org/10.1145/3488560.3498408openalex-snapshot
Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels
inferredcites →https://doi.org/10.1145/3543622.3573189openalex-snapshot
FNNG: A High-Performance FPGA-based Accelerator for K-Nearest Neighbor Graph Construction
inferredcites →https://doi.org/10.1145/3565973openalex-snapshot
Graph Neural Networks in IoT: A Survey
inferredcites →https://doi.org/10.1145/3568022openalex-snapshot
A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions
inferredcites →https://doi.org/10.1145/3637528openalex-snapshot
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
inferredcites →https://doi.org/10.1145/3729241openalex-snapshot
Learning on Missing Tabular Data: Attention with Self-Supervision, Not Imputation, is All You Need
inferredcites →https://doi.org/10.14778/3494124.3494128openalex-snapshot
xFraud
inferredcites →https://doi.org/10.1561/2200000096openalex-snapshot
Graph Neural Networks for Natural Language Processing: A Survey
inferredcites →https://doi.org/10.1609/aaai.v32i1.11604openalex-snapshot
Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning
inferredcites →https://doi.org/10.1609/aaai.v37i9.26272openalex-snapshot
T2G-FORMER: Organizing Tabular Features into Relation Graphs Promotes Heterogeneous Feature Interaction
inferredcites →https://doi.org/10.24963/ijcai.2021/630openalex-snapshot
Graph Learning based Recommender Systems: A Review
inferredcites →https://doi.org/10.24963/ijcai.2021/636openalex-snapshot
Deep Learning for Click-Through Rate Estimation
inferredcites →https://doi.org/10.24963/ijcai.2022/328openalex-snapshot
Regularized Graph Structure Learning with Semantic Knowledge for Multi-variates Time-Series Forecasting
inferredcites →https://doi.org/10.3233/faia240697openalex-snapshot
Interpretable Graph Neural Networks for Tabular Data
inferredcites →https://doi.org/10.3390/math9080830openalex-snapshot
k-Nearest Neighbor Learning with Graph Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.2106.06090openalex-snapshot
Graph Neural Networks for Natural Language Processing: A Survey
inferredcites →https://doi.org/10.48550/arxiv.2110.14377openalex-snapshot
Node Dependent Local Smoothing for Scalable Graph Learning

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-032-31526-7_31openalex-snapshot
Synthetic Identity Fraud Detection Using Federated Hybrid Graph Autoencoder—An AI-Based Approach
inferred← citeshttps://doi.org/10.1007/978-3-032-39518-4_39openalex-snapshot
G-TBI: Graph-Structured Ordinal Learning for TBI Outcome Prediction
inferred← citeshttps://doi.org/10.1007/978-981-96-5958-6_9openalex-snapshot
GNN-Based Disease Prediction Model
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Heterogeneous GNN-driven and meta-learned architecture for transparent multimodal string similarity estimation
inferred← citeshttps://doi.org/10.1007/s11760-026-05329-yopenalex-snapshot
k–GCNDFU: An explainable relational manifold learning framework for diabetic foot ulcer classification
inferred← citeshttps://doi.org/10.1016/j.aiopen.2025.08.004openalex-snapshot
Scalable graph attention-based instance selection via mini-batch sampling and hierarchical hashing
inferred← citeshttps://doi.org/10.1016/j.atech.2024.100743openalex-snapshot
A graph convolutional network approach for hyperspectral image analysis of blueberries physiological traits under drought stress
inferred← citeshttps://doi.org/10.1016/j.eswa.2025.131083openalex-snapshot
Dual-channel attention-autoencoder for tabular-graph fusion: tackling heterogeneous data in AI for Science
inferred← citeshttps://doi.org/10.1016/j.knosys.2026.116536openalex-snapshot
UA-Tab: Uncertainty-aware self-supervised representation learning for tabular data
inferred← citeshttps://doi.org/10.1109/access.2024.3437665openalex-snapshot
Graph Neural Networks for Individual Treatment Effect Estimation
inferred← citeshttps://doi.org/10.1109/aiotc71250.2026.11688502openalex-snapshot
Inductive Sample-Relation Augmentation for Simple Regression Models
inferred← citeshttps://doi.org/10.1109/ispa67752.2025.00076openalex-snapshot
RelGNN: A Relation-Embedding-Based Graph Neural Network for Tabular Data Imputation
inferred← citeshttps://doi.org/10.1140/epjs/s11734-024-01256-6openalex-snapshot
Interplay of traditional methods and machine learning algorithms for tagging boosted objects
inferred← citeshttps://doi.org/10.1177/14727978251358916openalex-snapshot
Group behavioral intention recognition based on semantic relations analysis
inferred← citeshttps://doi.org/10.1177/14727978251391340openalex-snapshot
Analysis of E-commerce user social network influence based on enhanced graph attention network algorithm
inferred← citeshttps://doi.org/10.20944/preprints202507.0515.v1openalex-snapshot
A Predictive Modeling Approach Based on Curriculum Meta-Learning and Attention-Enriched DeepFM for Sparse Data Scenarios
inferred← citeshttps://doi.org/10.2139/ssrn.5341184openalex-snapshot
A Study of Hybrid DeepFM Frameworks Enhanced with Self-Attention and Meta-Learning for Accurate Product Usage Forecasting
inferred← citeshttps://doi.org/10.2139/ssrn.5341186openalex-snapshot
A Comprehensive Review of DeepFM-Based Predictive Models with Integrated Attention Layers and Meta-Learning Approaches
inferred← citeshttps://doi.org/10.2139/ssrn.5341192openalex-snapshot
Development and Validation of a Lightweight DeepFM Model with Attention-Driven Feature Selection and Meta-Learning Tuning
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Exploring the Role of Dual Attention in DeepFM Networks Enhanced by Meta-Learning for E-Commerce Usage Prediction
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A Hybrid Ensemble Framework for Reliable and Interpretable Parkinson’s Disease Prediction Using Clinical Tabular Data
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