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  • Ma S. (2024). Retail store-SKU level replenishment planning with attribute-space graph recurrent neural networks. Expert Systems with Applications. 10.1016/j.eswa.2024.123727. 249. (123727). Online publication date: 1-Sep-2024.

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  • Boussaid T, Rousset F, Scuturici V and Clausse M. (2024). Enabling fast prediction of district heating networks transients via a physics-guided graph neural network. Applied Energy. 10.1016/j.apenergy.2024.123634. 370. (123634). Online publication date: 1-Sep-2024.

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  • Skarding J, Gabrys B and Musial K. On the Effectiveness of Heterogeneous Ensembles Combining Graph Neural Networks and Heuristics for Dynamic Link Prediction. IEEE Transactions on Network Science and Engineering. 10.1109/TNSE.2023.3343927. 11:4. (3250-3259).

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  • Zeng Z, Wang C, Ma F, Li X and Chen X. (2023). Incorporating self-attentions into robust spatial-temporal graph representation learning against dynamic graph perturbations. Computing. 106:7. (2211-2237). Online publication date: 1-Jul-2024.

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  • Rösch M, Nolde M, Ullmann T and Riedlinger T. (2024). Data-Driven Wildfire Spread Modeling of European Wildfires Using a Spatiotemporal Graph Neural Network. Fire. 10.3390/fire7060207. 7:6. (207).

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  • Laidi R, Djenouri D, Djenouri Y and Lin J. (2024). TG-SPRED: Temporal Graph for Sensorial Data PREDiction. ACM Transactions on Sensor Networks. 20:3. (1-20). Online publication date: 31-May-2024.

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  • Liu M, Tu Z, Su T, Wang X, Xu X and Wang Z. (2024). BehaviorNet: A Fine-grained Behavior-aware Network for Dynamic Link Prediction. ACM Transactions on the Web. 18:2. (1-26). Online publication date: 31-May-2024.

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  • Ntekouli M, Spanakis G, Waldorp L and Roefs A. (2024). Exploiting Individual Graph Structures to Enhance Ecological Momentary Assessment (EMA) Forecasting 2024 IEEE 40th International Conference on Data Engineering Workshops (ICDEW). 10.1109/ICDEW61823.2024.00027. 979-8-3503-8403-1. (158-166).

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  • Nagarajan S, Asha Jerlin M, Devarajan G, Sivakami R and Tiwari R. (2024). Efficiency Improvisation of Large-Scale Knowledge Systems in Feature Determination using Proposed HVGAN Architecture. Journal of Information & Knowledge Management. 10.1142/S0219649224500060. 23:02. Online publication date: 1-Apr-2024.

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  • Yin C, Jiang J, Wang Q, Mao Z and Jing N. DeltaGNN: Accelerating Graph Neural Networks on Dynamic Graphs With Delta Updating. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 10.1109/TCAD.2023.3335153. 43:4. (1163-1176).

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  • Gan Q, Yau W, Gan Y, Salam I, Guo S, Chang C, Wu Y and Zhou L. (2024). DSteganoM. Expert Systems with Applications: An International Journal. 238:PC. Online publication date: 15-Mar-2024.

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  • Wu R, Shen Z, Yang Z and Shu J. (2024). Mitigating Write Disturbance in Non-Volatile Memory via Coupling Machine Learning with Out-of-Place Updates 2024 IEEE International Symposium on High-Performance Computer Architecture (HPCA). 10.1109/HPCA57654.2024.00092. 979-8-3503-9313-2. (1184-1198).

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  • Zeng Z, Wang C, Ma F, Wang P and Wang H. (2023). Multiple-model and time-sensitive dynamic active learning for recurrent graph convolutional network model extraction attacks. International Journal of Machine Learning and Cybernetics. 10.1007/s13042-023-01916-4. 15:2. (383-404). Online publication date: 1-Feb-2024.

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  • Yu Y, Jiang X, Huang D, Li Y, Yue M and Zhao T. PIDGeuN: Graph Neural Network-Enabled Transient Dynamics Prediction of Networked Microgrids Through Full-Field Measurement. IEEE Access. 10.1109/ACCESS.2024.3384457. (1-1).

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  • Verdone A, Scardapane S and Panella M. (2024). Explainable Spatio-Temporal Graph Neural Networks for multi-site photovoltaic energy production. Applied Energy. 10.1016/j.apenergy.2023.122151. 353. (122151). Online publication date: 1-Jan-2024.

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  • Yang S, Zhou S, Yang S and Shi J. (2024). GFTLSTM: Dynamic Graph Neural Network Model Based on Graph Framelets Transform. Intelligent Technologies for Interactive Entertainment. 10.1007/978-3-031-55722-4_6. (63-75).

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  • Wu J, Huang J, Wu X and Dai H. (2023). A novel graph-based hybrid deep learning of cumulative GRU and deeper GCN for recognition of abnormal gait patterns using wearable sensors. Expert Systems with Applications: An International Journal. 233:C. Online publication date: 15-Dec-2023.

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  • Yu L, Sun L, Du B and Lv W. Towards better dynamic graph learning. Proceedings of the 37th International Conference on Neural Information Processing Systems. (67686-67700).

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  • Lin H, Yan M, Ye X, Fan D, Pan S, Chen W and Xie Y. A Comprehensive Survey on Distributed Training of Graph Neural Networks. Proceedings of the IEEE. 10.1109/JPROC.2023.3337442. 111:12. (1572-1606).

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  • Turner E and Cucuringu M. (2023). Graph Denoising Networks: A Deep Learning Framework for Equity Portfolio Construction ICAIF '23: 4th ACM International Conference on AI in Finance. 10.1145/3604237.3626903. 9798400702402. (193-201). Online publication date: 27-Nov-2023.

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  • Betancourt C, Li C, Kleinert F and Schultz M. (2023). Graph Machine Learning for Improved Imputation of Missing Tropospheric Ozone Data. Environmental Science & Technology. 10.1021/acs.est.3c05104. 57:46. (18246-18258). Online publication date: 21-Nov-2023.

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  • Fu K, Chen Q, Yang Y, Shi J, Li C and Guo M. BLAD: Adaptive Load Balanced Scheduling and Operator Overlap Pipeline For Accelerating The Dynamic GNN Training. Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. (1-13).

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  • Helm M, Jaeger B, Pfefferle C and Carle G. (2023). Beyond Mean: Spatio-Temporal Modeling of Queue Utilizations and Flow Latencies Using T-GNNs 2023 35th International Teletraffic Congress (ITC-35). 10.1109/ITC-3560063.2023.10555788. 979-8-3503-6007-3. (1-9).

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  • Choi I and Kim W. (2023). Estimating Historical Downside Risks of Global Financial Market Indices via Inflation Rate-Adjusted Dependence Graphs. Research in International Business and Finance. 10.1016/j.ribaf.2023.102077. 66. (102077). Online publication date: 1-Oct-2023.

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  • Jia Y, Wang J, Reza Hosseini M, Shou W, Wu P and Chao M. (2023). Temporal Graph Attention Network for Building Thermal Load Prediction. Energy and Buildings. 10.1016/j.enbuild.2023.113507. (113507). Online publication date: 1-Sep-2023.

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  • Xia Y, Zhang Z, Wang H, Yang D, Zhou X and Cheng D. Redundancy-Free High-Performance Dynamic GNN Training with Hierarchical Pipeline Parallelism. Proceedings of the 32nd International Symposium on High-Performance Parallel and Distributed Computing. (17-30).

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  • Ngo Q, Nguyen B, Vu T and Ngo T. (2023). State Estimation for Power Distribution System Using Graph Neural Networks 2023 IEEE Electric Ship Technologies Symposium (ESTS). 10.1109/ESTS56571.2023.10220523. 978-1-6654-6515-1. (441-446).

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  • Karimzadeh M and de Lima R. (2023). Deep Learning on SAR Imagery: Transfer Learning Versus Randomly Initialized Weights IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium. 10.1109/IGARSS52108.2023.10281892. 979-8-3503-2010-7. (1983-1986).

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  • Beeking M, Steinmaßl M, Urban M and Rehrl K. (2023). Sparse Data Traffic Speed Prediction on a Road Network With Varying Speed Levels. Transportation Research Record: Journal of the Transportation Research Board. 10.1177/03611981221148491. 2677:6. (448-465). Online publication date: 1-Jun-2023.

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  • Bai Y, Wang D, Huang G and Song B. A Deep-Reinforcement-Learning-Based Social-Aware Cooperative Caching Scheme in D2D Communication Networks. IEEE Internet of Things Journal. 10.1109/JIOT.2023.3234705. 10:11. (9634-9645).

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  • Fan Y, Yu X, Wieser R, Meakin D, Shaton A, Jaubert J, Flottemesch R, Howell M, Braid J, Bruckman L, French R and Wu Y. (2023). Spatio-Temporal Denoising Graph Autoencoders with Data Augmentation for Photovoltaic Data Imputation. Proceedings of the ACM on Management of Data. 1:1. (1-19). Online publication date: 26-May-2023.

    https://doi.org/10.1145/3588730

  • Mohammadiyeh S and Neysiani B. (2023). Analyzing and Improving Prediction of Spatiotemporal Signal Data Using Grid Search on Graph Convolutional Networks 2023 9th International Conference on Web Research (ICWR). 10.1109/ICWR57742.2023.10139174. 979-8-3503-9969-1. (294-299).

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  • Qin X, Sheikh N, Lei C, Reinwald B and Domeniconi G. (2023). SEIGN: A Simple and Efficient Graph Neural Network for Large Dynamic Graphs 2023 IEEE 39th International Conference on Data Engineering (ICDE). 10.1109/ICDE55515.2023.00218. 979-8-3503-2227-9. (2850-2863).

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  • Terroso Sáenz F, Arcas-Tunez F and Muñoz A. (2023). Nation-wide touristic flow prediction with Graph Neural Networks and heterogeneous open data. Information Fusion. 91:C. (582-597). Online publication date: 1-Mar-2023.

    https://doi.org/10.1016/j.inffus.2022.11.005

  • Karimzadeh M, Ngo T, Lucas B and Zoraghein H. (2023). Forecasting COVID-19 and Other Infectious Diseases for Proactive Policy: Artificial Intelligence Can Help. Journal of Urban Health. 10.1007/s11524-022-00714-7. 100:1. (7-10). Online publication date: 1-Feb-2023.

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  • Nguyen B, Vu T, Nguyen T, Panwar M and Hovsapian R. Spatial-Temporal Recurrent Graph Neural Networks for Fault Diagnostics in Power Distribution Systems. IEEE Access. 10.1109/ACCESS.2023.3273292. 11. (46039-46050).

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  • Iskandaryan D, Ramos F and Trilles S. Graph Neural Network for Air Quality Prediction: A Case Study in Madrid. IEEE Access. 10.1109/ACCESS.2023.3234214. 11. (2729-2742).

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  • Riedel A, Brehm N and Pfeifroth T. (2021). Hand Gesture Recognition of Methods-Time Measurement-1 Motions in Manual Assembly Tasks Using Graph Convolutional Networks. Applied Artificial Intelligence. 10.1080/08839514.2021.2014191. 36:1. Online publication date: 31-Dec-2022.

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  • Huang Y, Zheng L, Yao P, Wang Q, Liu H, Liao X, Jin H and Xue J. (2022). ReaDy: A ReRAM-Based Processing-in-Memory Accelerator for Dynamic Graph Convolutional Networks. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 41:11. (3567-3578). Online publication date: 1-Nov-2022.

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  • Hu S and Sukthankar G. (2022). Predicting Team Performance with Spatial Temporal Graph Convolutional Networks 2022 26th International Conference on Pattern Recognition (ICPR). 10.1109/ICPR56361.2022.9956457. 978-1-6654-9062-7. (2342-2348).

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  • Qureshi S, Hussain L, Alshahrani H, Abbas S, Nour M, Fatima N, Khalid M, Sohail H, Mohamed A and Hilal A. Gunshots Localization and Classification Model Based on Wind Noise Sensitivity Analysis Using Extreme Learning Machine. IEEE Access. 10.1109/ACCESS.2022.3198966. 10. (87302-87321).

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  • Sun A, Jiang P, Mudunuru M and Chen X. (2021). Explore Spatio‐Temporal Learning of Large Sample Hydrology Using Graph Neural Networks. Water Resources Research. 10.1029/2021WR030394. 57:12. Online publication date: 1-Dec-2021.

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