Copertina

Input Snapshots Fusion for Scalable Discrete-Time Dynamic Graph Neural Networks

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Qi, QingGuo, Chen, Hongyang, Cheng, Minhao, Liu, Han
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Linear-Time Graph Neural Networks for Scalable Recommendations
di: Zhang, Jiahao, et al.
Pubblicazione: (2024)

ScaleGNN: Towards Scalable Graph Neural Networks via Adaptive High-order Neighboring Feature Fusion
di: Li, Xiang, et al.
Pubblicazione: (2025)

DF-GNN: Dynamic Fusion Framework for Attention Graph Neural Networks on GPUs
di: Liu, Jiahui, et al.
Pubblicazione: (2024)

Ligandformer: A Graph Neural Network for Predicting Compound Property with Robust Interpretation
di: Guo, Jinjiang, et al.
Pubblicazione: (2022)

Graph Coarsening via Supervised Granular-Ball for Scalable Graph Neural Network Training
di: Xia, Shuyin, et al.
Pubblicazione: (2024)

HAGNN: Hybrid Aggregation for Heterogeneous Graph Neural Networks
di: Zhu, Guanghui, et al.
Pubblicazione: (2023)

Combinatorial Optimization with Automated Graph Neural Networks
di: Liu, Yang, et al.
Pubblicazione: (2024)

PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks
di: Su, Junwei, et al.
Pubblicazione: (2024)

Asymmetric Learning for Spectral Graph Neural Networks
di: Liu, Fangbing, et al.
Pubblicazione: (2024)

Decision-focused Graph Neural Networks for Combinatorial Optimization
di: Liu, Yang, et al.
Pubblicazione: (2024)

Scalable Quantum Error Mitigation with Physically Informed Graph Neural Networks
di: Wang, Huaxin, et al.
Pubblicazione: (2026)

How Interpretable Are Interpretable Graph Neural Networks?
di: Chen, Yongqiang, et al.
Pubblicazione: (2024)

Learning from Snapshots of Discrete and Continuous Data Streams
di: Devulapalli, Pramith, et al.
Pubblicazione: (2024)

When Graph Neural Networks Meet Dynamic Mode Decomposition
di: Shi, Dai, et al.
Pubblicazione: (2024)

Graph Neural Networks with Diversity-aware Neighbor Selection and Dynamic Multi-scale Fusion for Multivariate Time Series Forecasting
di: Xu, Jingqi, et al.
Pubblicazione: (2025)

MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation
di: Yu, Zhaoning, et al.
Pubblicazione: (2024)

Neural Network Graph Similarity Computation Based on Graph Fusion
di: Chang, Zenghui, et al.
Pubblicazione: (2025)

Generalized Discrete Diffusion from Snapshots
di: Zekri, Oussama, et al.
Pubblicazione: (2026)

Deep Neural Network Training as Random Effects: An Optimization-Inference Duality
di: Yao, Minhao, et al.
Pubblicazione: (2026)

PERTINENCE: Input-based Opportunistic Neural Network Dynamic Execution
di: Shende, Omkar, et al.
Pubblicazione: (2025)

Modelling Networked Dynamical System by Temporal Graph Neural ODE with Irregularly Partial Observed Time-series Data
di: Zou, Mengbang, et al.
Pubblicazione: (2024)

Minimize Control Inputs for Strong Structural Controllability Using Reinforcement Learning with Graph Neural Network
di: Zou, Mengbang, et al.
Pubblicazione: (2024)

TodyNet: Temporal Dynamic Graph Neural Network for Multivariate Time Series Classification
di: Liu, Huaiyuan, et al.
Pubblicazione: (2023)

Detecting High-Potential SMEs with Heterogeneous Graph Neural Networks
di: Qi, Yijiashun, et al.
Pubblicazione: (2026)

Full-Spectrum Graph Neural Networks: Expressive and Scalable
di: Wang, Xiaohan, et al.
Pubblicazione: (2026)

TimeCatcher: A Variational Framework for Volatility-Aware Forecasting of Non-Stationary Time Series
di: Chen, Zhiyu, et al.
Pubblicazione: (2026)

Fusion of Graph Neural Networks via Optimal Transport
di: Ormaniec, Weronika, et al.
Pubblicazione: (2025)

Dynamic Localisation of Spatial-Temporal Graph Neural Network
di: Duan, Wenying, et al.
Pubblicazione: (2025)

DTFormer: A Transformer-Based Method for Discrete-Time Dynamic Graph Representation Learning
di: Chen, Xi, et al.
Pubblicazione: (2024)

Uncertainty-Aware Graph Neural Networks: A Multi-Hop Evidence Fusion Approach
di: Chen, Qingfeng, et al.
Pubblicazione: (2025)

Sampling-guided Heterogeneous Graph Neural Network with Temporal Smoothing for Scalable Longitudinal Data Imputation
di: Zhang, Zhaoyang, et al.
Pubblicazione: (2024)

Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks
di: Trivedi, Puja, et al.
Pubblicazione: (2024)

GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks
di: Younesian, Taraneh, et al.
Pubblicazione: (2023)

Neural Clamping: Joint Input Perturbation and Temperature Scaling for Neural Network Calibration
di: Tang, Yung-Chen, et al.
Pubblicazione: (2022)

Advancing Single-Snapshot DOA Estimation with Siamese Neural Networks for Sparse Linear Arrays
di: Zheng, Ruxin, et al.
Pubblicazione: (2025)

Local Vertex Colouring Graph Neural Networks
di: Li, Shouheng, et al.
Pubblicazione: (2024)

Graph Neural Network Aided Deep Reinforcement Learning for Resource Allocation in Dynamic Terahertz UAV Networks
di: Hu, Zhifeng, et al.
Pubblicazione: (2025)

SAGDFN: A Scalable Adaptive Graph Diffusion Forecasting Network for Multivariate Time Series Forecasting
di: Jiang, Yue, et al.
Pubblicazione: (2024)

Designing Graph Convolutional Neural Networks for Discrete Choice with Network Effects
di: Villarraga, Daniel F., et al.
Pubblicazione: (2025)

Temperature Distribution Prediction in Laser Powder Bed Fusion using Transferable and Scalable Graph Neural Networks
di: Raut, Riddhiman, et al.
Pubblicazione: (2024)