Residual Correlation in Graph Neural Network Regression-Reference-Cited by-同舟云学术

Residual Correlation in Graph Neural Network Regression

Published:2020-07-06 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
language:
Short-container-title:

Author:

Jia Junteng¹,Benson Austion R.¹

Affiliation:

1. Cornell University, Ithaca, NY, USA

Funder

National Science Foundation

JPMorgan Chase and Company

Army Research Office

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3394486.3403101

Reference36 articles.

1. Rie Kubota Ando and Tong Zhang. 2006. Learning on Graph with Laplacian Regularization. In NeurIPS. Rie Kubota Ando and Tong Zhang. 2006. Learning on Graph with Laplacian Regularization. In NeurIPS.

2. Fan RK Chung and Fan Chung Graham. 1997. Spectral graph theory. Number 92. American Mathematical Soc. Fan RK Chung and Fan Chung Graham. 1997. Spectral graph theory. Number 92. American Mathematical Soc.

Cited by 21 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Spatio-Temporal Joint Graph Convolutional Networks for Traffic Forecasting;IEEE Transactions on Knowledge and Data Engineering;2024-01

2. An attentive Copula-based spatio-temporal graph model for multivariate time-series forecasting;Applied Soft Computing;2024-01

3. Graph-based methods for discrete choice;Network Science;2023-11-06

4. Graph Reasoning Method Based on Affinity Identification and Representation Decoupling for Predicting lncRNA-Disease Associations;Journal of Chemical Information and Modeling;2023-10-31

5. Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems;Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2023-08-04