mlsanityData to 7 Oct 2026

Explicit Feature Interaction-aware Graph Neural Networks

arXiv 2204.03225 ↗First posted 7 Apr 2022cs.LG cs.AIcited by 3

Not on the map. Why?

Abstract (arXiv)

Graph neural networks (GNNs) are powerful tools for handling graph-structured data. However, their design often limits them to learning only higher-order feature interactions, leaving low-order feature interactions overlooked. To address this problem, we introduce a novel GNN method called explicit feature interaction-aware graph neural network (EFI-GNN). Unlike conventional GNNs, EFI-GNN is a multilayer linear network designed to model arbitrary-order feature interactions explicitly within graphs. To validate the efficacy of EFI-GNN, we conduct experiments using various datasets. The experimental results demonstrate that EFI-GNN has competitive performance with existing GNNs, and when a GNN is jointly trained with EFI-GNN, predictive performance sees an improvement. Furthermore, the predictions made by EFI-GNN are interpretable, owing to its linear construction. The source code of EFI-GNN is available at https://github.com/gim4855744/EFI-GNN

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 36 of its 55 references that are in the map. First posted on arXiv 7 Apr 2022.

Builds on

36 of 55 references.

References · 36

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  3. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  4. 2017Graph Attention Networkscited by 8,854
  5. 2015Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shiftcited by 6,979
  6. 2017Inductive Representation Learning on Large Graphscited by 6,284
  7. 2014Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translationcited by 4,016
  8. 2019Fast Graph Representation Learning with PyTorch Geometriccited by 2,414
  9. 2020Open Graph Benchmark: Datasets for Machine Learning on Graphscited by 2,148
  10. 2019Simplifying Graph Convolutional Networkscited by 1,470
  11. 2017Neural Collaborative Filteringcited by 1,108
  12. 2018Pitfalls of Graph Neural Network Evaluationcited by 994
24 more
  1. 2016Revisiting Semi-Supervised Learning with Graph Embeddingscited by 970
  2. 2018Representation Learning on Graphs with Jumping Knowledge Networkscited by 875
  3. 2020Simple and Deep Graph Convolutional Networkscited by 857
  4. 2020Geom-GCN: Geometric Graph Convolutional Networkscited by 821
  5. 2021How Attentive are Graph Attention Networks?cited by 818
  6. 2015Gated Graph Sequence Neural Networkscited by 792
  7. 2016Wide & Deep Learning for Recommender Systemscited by 745
  8. 2019Graph Neural Networks for Social Recommendationcited by 711
  9. 2017DeepFM: A Factorization-Machine based Neural Network for CTR Predictioncited by 673
  10. 2018FastGCN: Fast Learning with Graph Convolutional Networks via Importance Samplingcited by 583
  11. 2019DeepGCNs: Can GCNs Go as Deep as CNNs?cited by 527
  12. 2019Graph Transformer Networkscited by 520
  13. 2017Deep & Cross Network for Ad Click Predictionscited by 392
  14. 2020Neural Additive Models: Interpretable Machine Learning with Neural Netscited by 318
  15. 2018xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systemscited by 277
  16. 2020DeeperGCN: All You Need to Train Deeper GCNscited by 249
  17. 2017Neural Factorization Machines for Sparse Predictive Analyticscited by 183
  18. 2018Adaptive Sampling Towards Fast Graph Representation Learningcited by 180
  19. 2019Inductive Matrix Completion Based on Graph Neural Networkscited by 85
  20. 2020How does this interaction affect me? Interpretable attribution for feature interactionscited by 73
  21. 2019Text Level Graph Neural Network for Text Classificationcited by 60
  22. 2019Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Predictioncited by 54
  23. 2021GraphFM: Graph Factorization Machines for Feature Interaction Modelingcited by 13
  24. 2019Feature Interaction-aware Graph Neural Networkscited by 3

Built on by

Cited by year

Citing papers per year: 2022: 1; 2023: 0; 2024: 1; 2025: 1.

3 papers.

  1. 2024Graph Neural Networks for Tabular Data Learning: A Survey with Taxonomy and Directionscited by 13
  2. 2022Higher-order Neural Additive Models: An Interpretable Machine Learning Model with Feature Interactionscited by 7
  3. 2025From Features to Graphs: Exploring Graph Structures and Pairwise Interactions via GNNscited by 0