Publications (19)
TimeSeriesBench: An Industrial-Grade Benchmark for Time Series Anomaly Detection Models
Haotian Si, Jianhui Li, Changhua Pei +9
Time series anomaly detection (TSAD) has gained significant attention due to its real-world applications to improve the stability of modern software systems. However, there is no e…
Virtual Node Generation for Node Classification in Sparsely-Labeled Graphs
Hang Cui, Tarek Abdelzaher
In the broader machine learning literature, data-generation methods demonstrate promising results by generating additional informative training examples via augmenting sparse label…
Three-dimensional quantum Griffiths singularity in bulk iron-pnictide superconductors
Shao-Bo Liu, Congkuan Tian, Yongqing Cai +15
The quantum Griffiths singularity (QGS) is a phenomenon driven by quenched disorders that break conventional scaling invariance and result in a divergent dynamical critical exponen…
ViTs: Teaching Machines to See Time Series Anomalies Like Human Experts
Zexin Wang, Changhua Pei, Yang Liu +8
Web service administrators must ensure the stability of multiple systems by promptly detecting anomalies in Key Performance Indicators (KPIs). Achieving the goal of "train once, in…
TShape: Rescuing Machine Learning Models from Complex Shapelet Anomalies
Hang Cui, Jingjing Li, Haotian Si +4
Time series anomaly detection (TSAD) is critical for maintaining the reliability of modern IT infrastructures, where complex anomalies frequently arise in highly dynamic environmen…
Quantum geometry induced anomalous chiral transport and hidden symmetry breaking in centrosymmetric 2M-WS2
Hang Cui, Shao-Bo Liu, Erqing Wang +16
Chirality, a widely existing material property in nature involving the breaking of the left-right symmetry, has profound influences in various fields of natural sciences. Nonlinear…