Chang Gong

According to our database, Chang Gong authored at least 16 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

A novel spatial-temporal graph convolution network based on temporal embedding graph structure learning for multivariate time series prediction.

Tianyang Lei, Jichao Li, Ke-Wei Yang, Chang Gong

Eng. Appl. Artif. Intell., 2025

2024

An unsupervised deep global-local views model for anomaly detection in attributed networks.

Tianyang Lei, Mengxin Ou, Chang Gong, Jichao Li, Ke-Wei Yang

Knowl. Based Syst., 2024

PORCA: Root Cause Analysis with Partially Observed Data.

Chang Gong, Di Yao, Jin Wang, Wenbin Li, Lanting Fang, Yongtao Xie, Kaiyu Feng, Peng Han, Jingping Bi

CoRR, 2024

STBench: Assessing the Ability of Large Language Models in Spatio-Temporal Analysis.

Wenbin Li, Di Yao, Ruibo Zhao, Wenjie Chen, Zijie Xu, Chengxue Luo, Chang Gong, Quanliang Jing, Haining Tan, Jingping Bi

CoRR, 2024

CausalMMM: Learning Causal Structure for Marketing Mix Modeling.

Chang Gong, Di Yao, Lei Zhang, Sheng Chen, Wenbin Li, Yueyang Su, Jingping Bi

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Towards Building a Lightweight and Powerful Computation Graph for Scalable GNN.

Chang Gong, Boyu Yang, Weiguo Zheng, Xing Huang, Weiyi Huang, Jie Wen, Shijie Sun, Bohua Yang

Proceedings of the Web Information Systems Engineering - WISE 2024, 2024

CausalTAD: Causal Implicit Generative Model for Debiased Online Trajectory Anomaly Detection.

Wenbin Li, Di Yao, Chang Gong, Xiaokai Chu, Quanliang Jing, Xiaolei Zhou, Yuxuan Zhang, Yunxia Fan, Jingping Bi

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

2023

A novel unsupervised framework for time series data anomaly detection via spectrum decomposition.

Tianyang Lei, Chang Gong, Gang Chen, Mengxin Ou, Ke-Wei Yang, Jichao Li

Knowl. Based Syst., November, 2023

Research on User Behavior Based on Higher-Order Dependency Network.

Liwei Qian, Yajie Dou, Chang Gong, Xiangqian Xu, Yuejin Tan

Entropy, August, 2023

Causal Discovery from Temporal Data: An Overview and New Perspectives.

Chang Gong, Di Yao, Chuzhe Zhang, Wenbin Li, Jingping Bi

CoRR, 2023

Causal Discovery from Temporal Data.

Chang Gong, Di Yao, Chuzhe Zhang, Wenbin Li, Jingping Bi, Lun Du, Jin Wang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022

Simulations of tumor growth and response to immunotherapy by coupling a spatial agent-based model with a whole-patient quantitative systems pharmacology model.

Alvaro Ruiz-Martinez, Chang Gong, Hanwen Wang, Richard J. Sové, Haoyang Mi, Holly Kimko, Aleksander S. Popel

PLoS Comput. Biol., 2022

CausalMTA: Eliminating the User Confounding Bias for Causal Multi-touch Attribution.

Di Yao, Chang Gong, Lei Zhang, Sheng Chen, Jingping Bi

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

TrajCross: Trajecotry Cross-Modal Retrieval with Contrastive Learning.

Quanliang Jing, Di Yao, Chang Gong, Xinxin Fan, Baoli Wang, Haining Tan, Jingping Bi

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Improved general attribute reduction algorithms.

Baizhen Li, Zhihua Wei, Duoqian Miao, Nan Zhang, Wen Shen, Chang Gong, Hongyun Zhang, Lijun Sun

Inf. Sci., 2020

2016

Computational and Empirical Studies Predict Mycobacterium tuberculosis-Specific T Cells as a Biomarker for Infection Outcome.

Simeone Marino, Hannah P. Gideon, Chang Gong, Shawn Mankad, John T. McCrone, Philana Ling Lin, Jennifer J. Linderman, JoAnne L. Flynn, Denise E. Kirschner

PLoS Comput. Biol., 2016