Saved in:
| Main Authors: | Liu, Zewen, Wang, Xiaoda, Wang, Bohan, Huang, Zijie, Yang, Carl, Jin, Wei |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.23167 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Integration of Graph Neural Network and Neural-ODEs for Tumor Dynamic Prediction
by: Bazgir, Omid, et al.
Published: (2023)
by: Bazgir, Omid, et al.
Published: (2023)
BrainODE: Dynamic Brain Signal Analysis via Graph-Aided Neural Ordinary Differential Equations
by: Han, Kaiqiao, et al.
Published: (2024)
by: Han, Kaiqiao, et al.
Published: (2024)
Graph Fourier Neural ODEs: Modeling Spatial-temporal Multi-scales in Molecular Dynamics
by: Sun, Fang, et al.
Published: (2024)
by: Sun, Fang, et al.
Published: (2024)
A Comprehensive Survey on Graph Summarization with Graph Neural Networks
by: Shabani, Nasrin, et al.
Published: (2023)
by: Shabani, Nasrin, et al.
Published: (2023)
Graph Neural Networks for Graphs with Heterophily: A Survey
by: Zheng, Xin, et al.
Published: (2022)
by: Zheng, Xin, et al.
Published: (2022)
A Review of Graph Neural Networks in Epidemic Modeling
by: Liu, Zewen, et al.
Published: (2024)
by: Liu, Zewen, et al.
Published: (2024)
Uncertainty in Graph Neural Networks: A Survey
by: Wang, Fangxin, et al.
Published: (2024)
by: Wang, Fangxin, et al.
Published: (2024)
Architecture-Aware Learning Curve Extrapolation via Graph Ordinary Differential Equation
by: Ding, Yanna, et al.
Published: (2024)
by: Ding, Yanna, et al.
Published: (2024)
On The Temporal Domain of Differential Equation Inspired Graph Neural Networks
by: Eliasof, Moshe, et al.
Published: (2024)
by: Eliasof, Moshe, et al.
Published: (2024)
A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware
by: Zhang, Shichang, et al.
Published: (2023)
by: Zhang, Shichang, et al.
Published: (2023)
Simulator and Experience Enhanced Diffusion Model for Comprehensive ECG Generation
by: Wang, Xiaoda, et al.
Published: (2025)
by: Wang, Xiaoda, et al.
Published: (2025)
Pre-training Epidemic Time Series Forecasters with Compartmental Prototypes
by: Liu, Zewen, et al.
Published: (2025)
by: Liu, Zewen, et al.
Published: (2025)
A Comprehensive Survey of Dynamic Graph Neural Networks: Models, Frameworks, Benchmarks, Experiments and Challenges
by: Feng, ZhengZhao, et al.
Published: (2024)
by: Feng, ZhengZhao, et al.
Published: (2024)
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
by: Dai, Enyan, et al.
Published: (2022)
by: Dai, Enyan, et al.
Published: (2022)
HAMLET: Graph Transformer Neural Operator for Partial Differential Equations
by: Bryutkin, Andrey, et al.
Published: (2024)
by: Bryutkin, Andrey, et al.
Published: (2024)
Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations
by: Bergna, Richard, et al.
Published: (2024)
by: Bergna, Richard, et al.
Published: (2024)
The Expressive Power of Graph Neural Networks: A Survey
by: Zhang, Bingxu, et al.
Published: (2023)
by: Zhang, Bingxu, et al.
Published: (2023)
Epidemiology-Aware Neural ODE with Continuous Disease Transmission Graph
by: Wan, Guancheng, et al.
Published: (2024)
by: Wan, Guancheng, et al.
Published: (2024)
HeteGraph-Mamba: Heterogeneous Graph Learning via Selective State Space Model
by: Pan, Zhenyu, et al.
Published: (2024)
by: Pan, Zhenyu, et al.
Published: (2024)
Exposing Vulnerabilities in Explanation for Time Series Classifiers via Dual-Target Attacks
by: Wang, Bohan, et al.
Published: (2026)
by: Wang, Bohan, et al.
Published: (2026)
DPAR: Decoupled Graph Neural Networks with Node-Level Differential Privacy
by: Zhang, Qiuchen, et al.
Published: (2022)
by: Zhang, Qiuchen, et al.
Published: (2022)
A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications
by: Han, Jiaqi, et al.
Published: (2024)
by: Han, Jiaqi, et al.
Published: (2024)
Implicit vs Unfolded Graph Neural Networks
by: Yang, Yongyi, et al.
Published: (2021)
by: Yang, Yongyi, et al.
Published: (2021)
Graph Pseudotime Analysis and Neural Stochastic Differential Equations for Analyzing Retinal Degeneration Dynamics and Beyond
by: Shi, Dai, et al.
Published: (2025)
by: Shi, Dai, et al.
Published: (2025)
Towards Comprehensive and Prerequisite-Free Explainer for Graph Neural Networks
by: Zhang, Han, et al.
Published: (2025)
by: Zhang, Han, et al.
Published: (2025)
Score-based Conditional Out-of-Distribution Augmentation for Graph Covariate Shift
by: Wang, Bohan, et al.
Published: (2024)
by: Wang, Bohan, et al.
Published: (2024)
Beyond Edge Deletion: A Comprehensive Approach to Counterfactual Explanation in Graph Neural Networks
by: De Sanctis, Matteo, et al.
Published: (2026)
by: De Sanctis, Matteo, et al.
Published: (2026)
Graph in Graph Neural Network
by: Wang, Jiongshu, et al.
Published: (2024)
by: Wang, Jiongshu, et al.
Published: (2024)
Differentiable Cluster Graph Neural Network
by: Dong, Yanfei, et al.
Published: (2024)
by: Dong, Yanfei, et al.
Published: (2024)
Graph Neural Networks in EEG-based Emotion Recognition: A Survey
by: Liu, Chenyu, et al.
Published: (2024)
by: Liu, Chenyu, et al.
Published: (2024)
Towards Complex Dynamic Physics System Simulation with Graph Neural ODEs
by: Shi, Guangsi, et al.
Published: (2023)
by: Shi, Guangsi, et al.
Published: (2023)
Large Language Models on Graphs: A Comprehensive Survey
by: Jin, Bowen, et al.
Published: (2023)
by: Jin, Bowen, et al.
Published: (2023)
PAGE: Parametric Generative Explainer for Graph Neural Network
by: Qiu, Yang, et al.
Published: (2024)
by: Qiu, Yang, et al.
Published: (2024)
Adversarial Training for Graph Neural Networks via Graph Subspace Energy Optimization
by: Liu, Ganlin, et al.
Published: (2024)
by: Liu, Ganlin, et al.
Published: (2024)
Incomplete Graph Learning: A Comprehensive Survey
by: Xia, Riting, et al.
Published: (2025)
by: Xia, Riting, et al.
Published: (2025)
Oversmoothing Alleviation in Graph Neural Networks: A Survey and Unified View
by: Jin, Yufei, et al.
Published: (2024)
by: Jin, Yufei, et al.
Published: (2024)
Hyperbolic-PDE GNN: Spectral Graph Neural Networks in the Perspective of A System of Hyperbolic Partial Differential Equations
by: Yue, Juwei, et al.
Published: (2025)
by: Yue, Juwei, et al.
Published: (2025)
A Survey of Lottery Ticket Hypothesis
by: Liu, Bohan, et al.
Published: (2024)
by: Liu, Bohan, et al.
Published: (2024)
GLL: A Differentiable Graph Learning Layer for Neural Networks
by: Brown, Jason, et al.
Published: (2024)
by: Brown, Jason, et al.
Published: (2024)
Graph Neural Networks for Protein-Protein Interactions -- A Short Survey
by: Xu, Mingda, et al.
Published: (2024)
by: Xu, Mingda, et al.
Published: (2024)
Similar Items
-
Integration of Graph Neural Network and Neural-ODEs for Tumor Dynamic Prediction
by: Bazgir, Omid, et al.
Published: (2023) -
BrainODE: Dynamic Brain Signal Analysis via Graph-Aided Neural Ordinary Differential Equations
by: Han, Kaiqiao, et al.
Published: (2024) -
Graph Fourier Neural ODEs: Modeling Spatial-temporal Multi-scales in Molecular Dynamics
by: Sun, Fang, et al.
Published: (2024) -
A Comprehensive Survey on Graph Summarization with Graph Neural Networks
by: Shabani, Nasrin, et al.
Published: (2023) -
Graph Neural Networks for Graphs with Heterophily: A Survey
by: Zheng, Xin, et al.
Published: (2022)