Zhijun Wang — Papers on Cortexa

arxivcs.LGcs.AI2026-06-27

RGLD: Randomized Global-Local Density Estimation for Tabular Anomaly Detection

Quanling Zhao, Jiaying Yang, Ye Tian, Josh Victoria, Zhijun Wang, Pietro Mercati, et al.

Unsupervised tabular anomaly detection requires methods that are accurate, robust across heterogeneous datasets, and computationally efficient. Classical statistical detectors are often efficient, but they usually rely on a fixed data view and a single notion of abnormality. Deep…

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crossrefInorganics2026-02-13Cited by 2

Comparation of Graph Neural Networks and Traditional Machine Learning for Property Prediction in All-Inorganic Perovskite Materials

Jingyu Liu, Xueqiong Su, Lishan Yang, Jiansen Ding, Jin Wang, Xing Ling, et al.

Machine learning (ML) methods have been widely explored for predicting material properties. However, due to the rapid development of ML techniques and the diversity of available models, performance comparisons between traditional and graph-based machine learning models remain lim…

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