Awesome GNN Architectures

Key papers

• Graph Neural Networks for Modeling Complex Dependencies in Global Supply Chain Networks (2026)
  Jingyi Liu et al.
  9.16
• Graph Neural Networks in Modern AI-aided Drug Discovery (2025)
  Odin Zhang et al.
  8.75
• An end-to-end attention-based approach for learning on graphs (2024)
  David Buterez et al.
  8.04
• Graph Kernel Neural Networks (2021)
  Luca Cosmo et al.
  7.59
• Multimodal Multi-Granularity Fusion Model with Mamba Architecture for Ames Mutagenicity Prediction. (2026)
  Tianming Han et al.
  7.24
• Adaptive Hyper-Graph Convolution Network for Skeleton-based Human Action Recognition with Virtual Connections (2024)
  Youwei Zhou and Tianyang Xu and Cong Wu and Xiaojun Wu and Josef Kittler
  6.85
• Social Network User Profiling for Anomaly Detection Based on Graph Neural Networks (2025)
  Yiwei Zhang
  6.69
• PepGraphormer: an ESM-GAT hybrid deep learning framework for antimicrobial peptide prediction (2026)
  Changhang Lin et al.
  6.52
• Blockchain Payment Fraud Detection with a Hybrid CNN-GNN-LSTM Model (2026)
  Haoran Zheng et al.
  6.52
• Graph Neural Networks for Knowledge Enhanced Visual Representation of Paintings (2021)
  Athanasios Efthymiou et al.
  6.39
• Incorporating Attributes and Multi-Scale Structures for Heterogeneous Graph Contrastive Learning (2025)
  Ruobing Jiang et al.
  6.23
• CureGraph: Contrastive Multi-Modal Graph Representation Learning for Urban Living Circle Health Profiling and Prediction (2025)
  Jinlin Li et al.
  6.12
• PyG 2.0: Scalable Learning on Real World Graphs (2025)
  Matthias Fey et al.
  5.87
• Efficient Learning of Mesh-Based Physical Simulation with BSMS-GNN (2022)
  Yadi Cao et al.
  5.84
• Graph Neural Network-Based Collaborative Perception for Adaptive Scheduling in Distributed Systems (2025)
  Wenxuan Zhu et al.
  5.76
• A Hierarchical Spatio-Temporal Graph Attention Network for False Data Injection Attack Detection in Smart Grids (2026)
  Hongjie Zhang et al.
  5.58
• Driving Decision-Making at Freeway Weaving Segments Using Relational Graph Attention Network and Deep Reinforcement Learning (2026)
  Zijin Wang et al.
  5.58
• Explaining GNN Explanations with Edge Gradients (2025)
  Jesse He et al.
  5.57
• When Design Rules Break: Benchmark Composition Determines Whether Label Informativeness Predicts GNN Aggregator Choice (2026)
  Neha Sharma et al.
  5.49
• Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention (2025)
  Van Thuy Hoang et al.
  5.35
• Recent Advances in Hypergraph Neural Networks (2025)
  Murong Yang et al.
  5.29
• Graph-CNNs for RF Imaging: Learning the Electric Field Integral Equations (2025)
  Kyriakos Stylianopoulos et al.
  5.29
• BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction (2025)
  Ruochen Li et al.
  5.24
• LiteFat: Lightweight Spatio-Temporal Graph Learning for Real-Time Driver Fatigue Detection (2025)
  Jing Ren et al.
  5.10
• Balancing Graph Embedding Smoothness in Self-Supervised Learning via Information-Theoretic Decomposition (2025)
  Heesoo Jung et al.
  4.93
• Uncertainty-Aware Graph Structure Learning (2025)
  Shen Han et al.
  4.82
• X-Node: Self-Explanation is All We Need (2025)
  Prajit Sengupta and Islem Rekik
  4.78
• Graph Learning (2025)
  Feng Xia et al.
  4.58
• DistMLIP: A Distributed Inference Platform for Machine Learning Interatomic Potentials (2025)
  Kevin Han et al.
  4.53
• Generalizing Graph Foundation Models via Hyperbolic Retrieval-Augmented Generation (2026)
  Yifan Jin et al.
  4.39
• SpliceBind: Isoform-Aware Prediction of Binding Pocket Druggability (2026)
  Bryan Cheng et al.
  4.39
• Structure-Aware Prediction of PROTAC-Mediated Protein Degradability via Graph Neural Networks (2026)
  Bryan Cheng et al.
  4.39
• Bayesian Membership Privacy for Graph Neural Networks (2026)
  Sinan Y{\i}ld{\i}r{\i}m et al.
  4.39
• Scaling Novel Graph Generation via Lightweight Structure-Guided Autoregressive Models (2026)
  Alessio Barboni et al.
  4.39
• SFMambaNet: Spectral-Frequency Enhanced Selective State Space Model for Correspondence Pruning (2026)
  Zhihua Wang et al.
  4.39
• Graph Cascades: Contagion-Based Mesoscopic Rewiring for Structure-Aware Graph Machine Learning (2026)
  Meher Chaitanya et al.
  4.39
• Graph Set Transformer (2026)
  Jose E. Escrig Molina et al.
  4.39
• Spatiotemporal Imputation with Graph-Informed Flow Matching (2026)
  Zepeng Zhang et al.
  4.39
• Graph Neural Network leveraging Higher-order Class Label Connectivity for Heterophilous Graphs (2026)
  Takuto Takahashi et al.
  4.39
• Revisiting Positive Samples in Graph Contrastive Learning: From the Perspective of Message Passing (2026)
  Lianze Shan et al.
  4.39
• ERAlign: Energy-based Representation Alignment of GNNs and LLMs on Text-attributed Graphs (2026)
  Xianlin Zeng et al.
  4.39
• Non-linear mechanical field reconstruction coupling recurrent neural networks with physics-informed graph neural networks (2026)
  Manuel Ricardo Guevara Garban et al.
  4.39
• COGENT: Continuous Graph Emulators with Neural Ordinary Differential Equations for Long-Term Physical Forecasting (2026)
  Zesheng Liu et al.
  4.39
• GLACIER: A Multimodal Student-Teacher Foundation Model for Molecular Property Prediction (2026)
  Emily Nguyen et al.
  4.39
• LLMs+Graphs: Toward Graph-Native, Synergistic AI Systems (2026)
  Arijit Khan et al.
  4.39
• From Uniform to Learned Graph Priors: Diffusion for Structure Discovery (2026)
  Qi Shao et al.
  4.39
• Temporally Consistent Graph Q-Networks for Intelligent Network Control (2026)
  Zacharias Veiksaar et al.
  4.39
• Curvature-Informed Potential Energy Surface for Protein-Ligand Binding Affinity Prediction (2026)
  Peng-Fei Sun et al.
  4.39
• Artemis: Anatomy-Resolved inTervention for Eliminating Multimodal NeuroImage confounderS (2026)
  Siyuan Dai et al.
  4.39
• Enhanced Graph Neural Networks using K-Hop Gaussian Diffusion (2026)
  Xuling Zhang et al.
  4.39
• RankGraph-2: Lifecycle Co-Design for Billion-Node Graph Learning in Recommendation (2026)
  Renzhi Wu et al.
  4.39
• TMR-GGNN: Credit Card Fraud Detection based on Time-Aware Multi-Relational Guided Graph Neural Network (2026)
  Rohit Tewari et al.
  4.39
• AGDN: Learning to Solve Traveling Salesman Problem with Anisotropic Graph Diffusion Network (2026)
  Bolin Shen et al.
  4.39
• P-K-GCN: Physics-augmented Koopman-enhanced Graph Convolutional Network for Deep Spatiotemporal Super-resolution (2026)
  Xizhuo (Cici) et al.
  4.39
• GOProteinGNN: Leveraging Protein Knowledge Graphs for Protein Representation Learning (2024)
  Dan Kalifa et al.
  4.36
• CIMAGE: Exploiting the Conditional Independence in Masked Graph Auto-encoders (2025)
  Jongwon Park et al.
  4.36
• Graph-Driven Cross-Industry Real-Time Monitoring Framework for Anti-Money Laundering Detection in Converged Mobility-Energy Supply Chain Networks (2026)
  Rong Liu et al.
  4.33
• Projecting Latent RL Actions: Towards Generalizable and Scalable Graph Combinatorial Optimization (2026)
  Franco Terranova (UL et al.
  4.33
• Graph Navier Stokes Networks (2026)
  Zexing Zhao et al.
  4.33
• Gaussian Sheaf Neural Networks (2026)
  Andr\'e Ribeiro et al.
  4.33