Publications

2024

Efficiently Predicting Mutational Effect on Homologous Proteins by Evolution Encoding
Zhiqiang Zhong, Davide Mottin.
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD’24) [Paper] [Code]
Harnessing Large Language Models as Post-hoc Correctors
Zhiqiang Zhong, Kuangyu Zhou, Davide Mottin.
The Annual Meeting of the Association for Computational Linguistics (ACL’24) [Paper] [Code]
Benchmarking Large Language Models for Molecule Prediction Tasks.
Zhiqiang Zhong, Kuangyu Zhou, Davide Mottin.
Preprint on arxiv [Paper] [Code]
Hierarchical Bipartite Graph Convolutional Network for Recommendation
Yi Wei Cheng, Zhiqiang Zhong, Jun Pang, Cheng-Te Li.
IEEE Computational Intelligence Magazine (CIM) [Paper] [Code]
Bridging Performance of X (formerly known as Twitter) Users: A Predictor of Subjective Well-Being During the Pandemic
Ninghan Chen, Xihui Chen, Zhiqiang Zhong, Jun Pang.
ACM Transactions on the Web [Paper] [Code]

On the Robustness of Post-hoc GNN Explainers to Label Noise.
Zhiqiang Zhong, Yangqianzi Jiang, Davide Mottin
Learning on Graphs Conference (LoG’23) [Paper] [Code]
How Faithful are Self-Explainable GNNs?
Marc Christiansen, Lea Villadsen, Zhiqiang Zhong, Stefano Teso, Davide Mottin.
Learning on Graphs Conference (LoG’23) [Paper] [Code]
Tutorial: Knowledge-augmented Graph Machine Learning for Drug Discovery: From Precision to Interpretability
Zhiqiang Zhong, Davide Mottin
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’23) [Paper] [Web Page]
Multi-grained Semantics-aware Graph Neural Networks
Zhiqiang Zhong, Cheng-Te Li, Jun Pang
IEEE Transactions on Knowledge and Data Engineering (TKDE) [Paper] [Code]
Knowledge-augmented Graph Machine Learning for Drug Discovery: A Survey from Precision to Interpretability
Zhiqiang Zhong, Anastasia Barkova, Davide Mottin
Preprint on arxiv [Paper] [GitHub Page]
Hierarchical Message-Passing Graph Neural Networks
Zhiqiang Zhong, Cheng-Te Li, Jun Pang
Journal of Data Mining and Knowledge Discovery (DMKD) - Journal Track of ECML-PKDD [Paper] [Code]

Unsupervised Network Embedding Beyond Homophily
Zhiqiang Zhong, Guadalupe Gonzalez, Daniele Grattarola, Jun Pang
Transactions on Machine Learning Research (TMLR) [Paper] [Code]
Simplifying Node Classification on Heterophilous Graphs with Compatible Label Propagation
Zhiqiang Zhong, Sergey Ivanov, Jun Pang
Transactions on Machine Learning Research (TMLR) [Paper] [Code]
The Burden of Being a Bridge: Analysing Subjective Well-Being of Twitter Users during the COVID-19 Pandemic
Ninghan Chen, Xihui Chen, Zhiqiang Zhong, Jun Pang
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD’22) [Paper]
Leveraging Graph Machine Learning for Social Network Analysis
Zhiqiang Zhong
PhD. Degree Thesis Published at orbilu.uni.lu [Paper]
Personalised Meta-path Generation for Heterogeneous Graph Neural Networks
Zhiqiang Zhong, Cheng-Te Li, Jun Pang
Journal of Data Mining and Knowledge Discovery (DMKD) - Journal Track of ECML-PKDD [Paper [Code]
Exploring Spillover Effects for COVID-19 Cascade Prediction
Ninghan Chen, Xihui Chen, Zhiqiang Zhong, Jun Pang
Journal of Entropy [Paper]

From #Jobsearch to #Mask: Improving COVID-19 Cascade Prediction with Spillover Effects
Ninghan Chen, Xihui Chen, Zhiqiang Zhong, Jun Pang
ACM/IEEE International Conference on Social Network Analysis and Mining (ASONAM’21) [Paper]
An Exploratory Study of COVID-19 Information on Twitter in the Greater Region
Ninghan Chen, Zhiqiang Zhong, Jun Pang
Journal of Big Data and Cognitive Computing [Paper]

NeuLP: An End-to-end Deep-learning Model for Link Prediction
Zhiqiang Zhong, Yang Zhang, Jun Pang
In Proceedings of the 21th International Conference on Web Information Systems Engineering (WISE’20) [Paper] [Code]

A Graph-based Approach to Explore Relationship between Hashtags and Images
Zhiqiang Zhong, Yang Zhang, Jun Pang
In Proceedings of the 20th International Conference on Web Information Systems Engineering (WISE’19) [Paper]