GNN Papers
Updated on 2025.08.02
| Publish Date | Title | Authors | Code | |
|---|---|---|---|---|
| 2025-07-21 | Learning nuclear cross sections across the chart of nuclides with graph neural networks | Hongjun Choi et.al. | 2404.02332 | null |
| 2025-07-18 | Binarizing Physics-Inspired GNNs for Combinatorial Optimization | Martin Krutský et.al. | 2507.13703 | null |
| 2025-07-08 | DAFOS: Dynamic Adaptive Fanout Optimization Sampler | Irfan Ullah et.al. | 2507.08845 | null |
| 2025-06-26 | Accelerating GNN Training through Locality-aware Dropout and Merge | Gongjian Sun et.al. | 2506.21414 | null |
| 2025-06-25 | Demystifying Distributed Training of Graph Neural Networks for Link Prediction | Xin Huang et.al. | 2506.20818 | null |
| 2025-06-17 | Delving into Instance-Dependent Label Noise in Graph Data: A Comprehensive Study and Benchmark | Suyeon Kim et.al. | 2506.12468 | link |
| 2025-06-14 | Optimizing Federated Learning using Remote Embeddings for Graph Neural Networks | Pranjal Naman et.al. | 2506.12425 | null |
| 2025-06-13 | Graph Semi-Supervised Learning for Point Classification on Data Manifolds | Caio F. Deberaldini Netto et.al. | 2506.12197 | null |
| 2025-06-06 | Generalization of Geometric Graph Neural Networks with Lipschitz Loss Functions | Zhiyang Wang et.al. | 2409.05191 | null |
| 2025-05-27 | Simple yet Effective Graph Distillation via Clustering | Yurui Lai et.al. | 2505.20807 | null |
| 2025-05-26 | Towards Efficient Training of Graph Neural Networks: A Multiscale Approach | Eshed Gal et.al. | 2503.19666 | null |
| 2025-05-26 | Scaling Large-scale GNN Training to Thousands of Processors on CPU-based Supercomputers | Chen Zhuang et.al. | 2411.16025 | null |
| 2025-05-22 | Semi-decentralized Training of Spatio-Temporal Graph Neural Networks for Traffic Prediction | Ivan Kralj et.al. | 2412.03188 | null |
| 2025-05-16 | RapidGNN: Communication Efficient Large-Scale Distributed Training of Graph Neural Networks | Arefin Niam et.al. | 2505.10806 | null |
| 2025-05-15 | FedGRec: Dynamic Spatio-Temporal Federated Graph Learning for Secure and Efficient Cross-Border Recommendations | Zhizhong Tan et.al. | 2505.18177 | null |
| 2025-05-13 | COMRECGC: Global Graph Counterfactual Explainer through Common Recourse | Gregoire Fournier et.al. | 2505.07081 | link |
| 2025-05-11 | QSeer: A Quantum-Inspired Graph Neural Network for Parameter Initialization in Quantum Approximate Optimization Algorithm Circuits | Lei Jiang et.al. | 2505.06810 | null |
| 2025-05-11 | RobGC: Towards Robust Graph Condensation | Xinyi Gao et.al. | 2406.13200 | null |
| 2025-05-07 | Plexus: Taming Billion-edge Graphs with 3D Parallel GNN Training | Aditya K. Ranjan et.al. | 2505.04083 | null |
| 2025-04-25 | Efficient GNN Training Through Structure-Aware Randomized Mini-Batching | Vignesh Balaji et.al. | 2504.18082 | null |
| 2025-04-17 | Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs | Zichao Yue et.al. | 2504.13266 | link |
| 2025-04-16 | Federated Spectral Graph Transformers Meet Neural Ordinary Differential Equations for Non-IID Graphs | Kishan Gurumurthy et.al. | 2504.11808 | link |
| 2025-04-07 | Sparsity-Aware Communication for Distributed Graph Neural Network Training | Ujjaini Mukhodopadhyay et.al. | 2504.04673 | null |
| 2025-04-07 | Scaling Graph Neural Networks for Particle Track Reconstruction | Alok Tripathy et.al. | 2504.04670 | link |
| 2025-03-31 | Graph neural networks extrapolate out-of-distribution for shortest paths | Robert R. Nerem et.al. | 2503.19173 | null |
| 2025-03-31 | Backdoor Graph Condensation | Jiahao Wu et.al. | 2407.11025 | link |
| 2025-03-29 | DP-GPL: Differentially Private Graph Prompt Learning | Jing Xu et.al. | 2503.10544 | null |
| 2025-03-24 | Deterministic Certification of Graph Neural Networks against Graph Poisoning Attacks with Arbitrary Perturbations | Jiate Li et.al. | 2503.18503 | link |
| 2025-03-19 | Lyapunov-Based Graph Neural Networks for Adaptive Control of Multi-Agent Systems | Brandon C. Fallin et.al. | 2503.15360 | null |
| 2025-03-04 | Deal: Distributed End-to-End GNN Inference for All Nodes | Shiyang Chen et.al. | 2503.02960 | null |
| 2025-03-04 | Node-level Contrastive Unlearning on Graph Neural Networks | Hong kyu Lee et.al. | 2503.02959 | null |
| 2025-02-26 | Graph Neural Networks embedded into Margules model for vapor-liquid equilibria prediction | Edgar Ivan Sanchez Medina et.al. | 2502.18998 | link |
| 2025-02-25 | Armada: Memory-Efficient Distributed Training of Large-Scale Graph Neural Networks | Roger Waleffe et.al. | 2502.17846 | null |
| 2025-02-24 | Detecting Code Vulnerabilities with Heterogeneous GNN Training | Yu Luo et.al. | 2502.16835 | null |
| 2025-02-23 | Subsampling Graphs with GNN Performance Guarantees | Mika Sarkin Jain et.al. | 2502.16703 | null |
| 2025-02-21 | Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph Learning | Xingbo Fu et.al. | 2412.19229 | link |
| 2025-02-18 | Unveiling Mode Connectivity in Graph Neural Networks | Bingheng Li et.al. | 2502.12608 | null |
| 2025-02-15 | A Distillation-based Future-aware Graph Neural Network for Stock Trend Prediction | Zhipeng Liu et.al. | 2502.10776 | null |
| 2025-02-15 | DiskGNN: Bridging I/O Efficiency and Model Accuracy for Out-of-Core GNN Training | Renjie Liu et.al. | 2405.05231 | null |
| 2025-02-14 | The Graph’s Apprentice: Teaching an LLM Low Level Knowledge for Circuit Quality Estimation | Reza Moravej et.al. | 2411.00843 | null |
| 2025-01-23 | Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition | Xinyi Gao et.al. | 2405.13707 | link |
| 2025-01-05 | Efficient Graph Condensation via Gaussian Process | Lin Wang et.al. | 2501.02565 | link |
| 2024-12-29 | NeutronTP: Load-Balanced Distributed Full-Graph GNN Training with Tensor Parallelism | Xin Ai et.al. | 2412.20379 | null |
| 2024-12-23 | Attack by Yourself: Effective and Unnoticeable Multi-Category Graph Backdoor Attacks with Subgraph Triggers Pool | Jiangtong Li et.al. | 2412.17213 | null |
| 2024-12-20 | Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch | Saurabh Bajaj et.al. | 2406.00552 | null |
| 2024-12-19 | Grimm: A Plug-and-Play Perturbation Rectifier for Graph Neural Networks Defending against Poisoning Attacks | Ao Liu et.al. | 2412.08555 | null |
| 2024-12-12 | HC-SpMM: Accelerating Sparse Matrix-Matrix Multiplication for Graphs with Hybrid GPU Cores | Zhonggen Li et.al. | 2412.08902 | null |
| 2024-12-06 | Code generation and runtime techniques for enabling data-efficient deep learning training on GPUs | Kun Wu et.al. | 2412.04747 | null |
| 2024-11-26 | Contrastive Graph Condensation: Advancing Data Versatility through Self-Supervised Learning | Xinyi Gao et.al. | 2411.17063 | null |
| 2024-11-19 | Efficient Model-Stealing Attacks Against Inductive Graph Neural Networks | Marcin Podhajski et.al. | 2405.12295 | link |
| 2024-11-19 | On Size and Hardness Generalization in Unsupervised Learning for the Travelling Salesman Problem | Yimeng Min et.al. | 2403.20212 | null |
| 2024-11-17 | Training a Label-Noise-Resistant GNN with Reduced Complexity | Rui Zhao et.al. | 2411.11020 | link |
| 2024-11-15 | Graph Neural Networks and Differential Equations: A hybrid approach for data assimilation of fluid flows | M. Quattromini et.al. | 2411.09476 | null |
| 2024-11-12 | Rethinking Structure Learning For Graph Neural Networks | Yilun Zheng et.al. | 2411.07672 | null |
| 2024-11-08 | YOSO: You-Only-Sample-Once via Compressed Sensing for Graph Neural Network Training | Yi Li et.al. | 2411.05693 | null |
| 2024-11-05 | Distributed Graph Neural Network Design for Sum Ergodic Spectral Efficiency Maximization in Cell-Free Massive MIMO | Nguyen Xuan Tung et.al. | 2411.02900 | null |
| 2024-11-03 | MassiveGNN: Efficient Training via Prefetching for Massively Connected Distributed Graphs | Aishwarya Sarkar et.al. | 2410.22697 | link |
| 2024-11-02 | Using Half-Precision for GNN Training | Arnab Kanti Tarafder et.al. | 2411.01109 | null |
| 2024-10-29 | Vision Paper: Designing Graph Neural Networks in Compliance with the European Artificial Intelligence Act | Barbara Hoffmann et.al. | 2410.22120 | null |
| 2024-10-28 | Graph Sparsification for Enhanced Conformal Prediction in Graph Neural Networks | Yuntian He et.al. | 2410.21618 | null |
| 2024-10-25 | Gradient Rewiring for Editable Graph Neural Network Training | Zhimeng Jiang et.al. | 2410.15556 | link |
| 2024-10-22 | Fast Graph Sharpness-Aware Minimization for Enhancing and Accelerating Few-Shot Node Classification | Yihong Luo et.al. | 2410.16845 | link |
| 2024-10-09 | TCGU: Data-centric Graph Unlearning based on Transferable Condensation | Fan Li et.al. | 2410.06480 | null |
| 2024-10-09 | RoCP-GNN: Robust Conformal Prediction for Graph Neural Networks in Node-Classification | S. Akansha et.al. | 2408.13825 | null |
| 2024-10-07 | Haste Makes Waste: A Simple Approach for Scaling Graph Neural Networks | Rui Xue et.al. | 2410.05416 | null |
| 2024-10-07 | BSG4Bot: Efficient Bot Detection based on Biased Heterogeneous Subgraphs | Hao Miao et.al. | 2410.05356 | null |
| 2024-10-02 | Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling | Shivam Barwey et.al. | 2410.01657 | null |
| 2024-10-01 | LinkThief: Combining Generalized Structure Knowledge with Node Similarity for Link Stealing Attack against GNN | Yuxing Zhang et.al. | 2410.02826 | null |
| 2024-09-29 | One Node Per User: Node-Level Federated Learning for Graph Neural Networks | Zhidong Gao et.al. | 2409.19513 | null |
| 2024-09-23 | FastGL: A GPU-Efficient Framework for Accelerating Sampling-Based GNN Training at Large Scale | Zeyu Zhu et.al. | 2409.14939 | link |
| 2024-09-17 | Can Graph Reordering Speed Up Graph Neural Network Training? An Experimental Study | Nikolai Merkel et.al. | 2409.11129 | link |
| 2024-09-10 | Generalization of Graph Neural Networks is Robust to Model Mismatch | Zhiyang Wang et.al. | 2408.13878 | null |
| 2024-09-08 | HopGNN: Boosting Distributed GNN Training Efficiency via Feature-Centric Model Migration | Weijian Chen et.al. | 2409.00657 | null |
| 2024-08-21 | Slicing Input Features to Accelerate Deep Learning: A Case Study with Graph Neural Networks | Zhengjia Xu et.al. | 2408.11500 | null |
| 2024-08-20 | Heta: Distributed Training of Heterogeneous Graph Neural Networks | Yuchen Zhong et.al. | 2408.09697 | null |
| 2024-08-01 | CDFGNN: a Systematic Design of Cache-based Distributed Full-Batch Graph Neural Network Training with Communication Reduction | Shuai Zhang et.al. | 2408.00232 | null |
| 2024-07-21 | LSM-GNN: Large-scale Storage-based Multi-GPU GNN Training by Optimizing Data Transfer Scheme | Jeongmin Brian Park et.al. | 2407.15264 | null |
| 2024-07-18 | Predicting dark matter halo masses from simulated galaxy images and environments | Austin J. Larson et.al. | 2407.13735 | null |
| 2024-07-18 | MSPipe: Efficient Temporal GNN Training via Staleness-Aware Pipeline | Guangming Sheng et.al. | 2402.15113 | link |
| 2024-07-17 | GraphMuse: A Library for Symbolic Music Graph Processing | Emmanouil Karystinaios et.al. | 2407.12671 | link |
| 2024-07-12 | Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective | Zhiwei Zhang et.al. | 2405.10757 | link |
| 2024-07-10 | TinyGraph: Joint Feature and Node Condensation for Graph Neural Networks | Yezi Liu et.al. | 2407.08064 | link |
| 2024-07-10 | STAGE: Simplified Text-Attributed Graph Embeddings Using Pre-trained LLMs | Aaron Zolnai-Lucas et.al. | 2407.12860 | link |
| 2024-07-09 | On the Robustness of Graph Reduction Against GNN Backdoor | Yuxuan Zhu et.al. | 2407.02431 | null |
| 2024-07-03 | ITEM: Improving Training and Evaluation of Message-Passing based GNNs for top-k recommendation | Yannis Karmim et.al. | 2407.07912 | null |
| 2024-06-25 | Distributed Training of Large Graph Neural Networks with Variable Communication Rates | Juan Cervino et.al. | 2406.17611 | null |
| 2024-06-20 | Reducing Memory Contention and I/O Congestion for Disk-based GNN Training | Qisheng Jiang et.al. | 2406.13984 | link |
| 2024-06-18 | Pretraining Strategy for Neural Potentials | Zehua Zhang et.al. | 2402.15921 | link |
| 2024-06-15 | HiFGL: A Hierarchical Framework for Cross-silo Cross-device Federated Graph Learning | Zhuoning Guo et.al. | 2406.10616 | link |
| 2024-06-12 | Graph Condensation for Open-World Graph Learning | Xinyi Gao et.al. | 2405.17003 | null |
| 2024-06-07 | SpanGNN: Towards Memory-Efficient Graph Neural Networks via Spanning Subgraph Training | Xizhi Gu et.al. | 2406.04938 | link |
| 2024-06-06 | LOGIN: A Large Language Model Consulted Graph Neural Network Training Framework | Yiran Qiao et.al. | 2405.13902 | link |
| 2024-06-05 | Real-Time Small-Signal Security Assessment Using Graph Neural Networks | Glory Justin et.al. | 2406.02964 | null |
| 2024-05-27 | Spectral Greedy Coresets for Graph Neural Networks | Mucong Ding et.al. | 2405.17404 | null |
| 2024-05-21 | Unleash Graph Neural Networks from Heavy Tuning | Lequan Lin et.al. | 2405.12521 | null |
| 2024-05-10 | Disttack: Graph Adversarial Attacks Toward Distributed GNN Training | Yuxiang Zhang et.al. | 2405.06247 | link |
| 2024-05-01 | A Comprehensive Survey of Dynamic Graph Neural Networks: Models, Frameworks, Benchmarks, Experiments and Challenges | ZhengZhao Feng et.al. | 2405.00476 | null |
| 2024-04-26 | FlowWalker: A Memory-efficient and High-performance GPU-based Dynamic Graph Random Walk Framework | Junyi Mei et.al. | 2404.08364 | link |
| 2024-04-15 | GNNavigator: Towards Adaptive Training of Graph Neural Networks via Automatic Guideline Exploration | Tong Qiao et.al. | 2404.09544 | null |
| 2024-04-02 | CATGNN: Cost-Efficient and Scalable Distributed Training for Graph Neural Networks | Xin Huang et.al. | 2404.02300 | null |
| 2024-03-25 | A Unified CPU-GPU Protocol for GNN Training | Yi-Chien Lin et.al. | 2403.17092 | link |
| 2024-03-22 | Task-Oriented GNNs Training on Large Knowledge Graphs for Accurate and Efficient Modeling | Hussein Abdallah et.al. | 2403.05752 | link |
| 2024-03-21 | iSpLib: A Library for Accelerating Graph Neural Networks using Auto-tuned Sparse Operations | Md Saidul Hoque Anik et.al. | 2403.14853 | link |
| 2024-03-16 | Edge Private Graph Neural Networks with Singular Value Perturbation | Tingting Tang et.al. | 2403.10995 | null |