6 papers
An Encode-then-Decompose Approach to Unsupervised Time Series Anomaly Detection on Contaminated Training Data--Extended Version
Buang Zhang, Tung Kieu, Xiangfei Qiu +5
Time series anomaly detection is important in modern large-scale systems and is applied in a variety of domains to analyze and monitor the operation of diverse systems. Unsupervise…
TAB: Unified Benchmarking of Time Series Anomaly Detection Methods
Xiangfei Qiu, Zhe Li, Wanghui Qiu +10
Time series anomaly detection (TSAD) plays an important role in many domains such as finance, transportation, and healthcare. With the ongoing instrumentation of reality, more time…
Zero-Knowledge Verifiable Graph Query Evaluation via Expansion-Centric Operator Decomposition
Hao Wu, Changzheng Wei, Yanhao Wang +7
This paper investigates the feasibility of achieving zero-knowledge verifiability for graph databases, enabling database owners to cryptographically prove the query execution corre…
TSFM-Bench: A Comprehensive and Unified Benchmark of Foundation Models for Time Series Forecasting
Zhe Li, Xiangfei Qiu, Peng Chen +8
Time Series Forecasting (TSF) is key functionality in numerous fields, such as financial investment, weather services, and energy management. Although increasingly capable TSF meth…
Air Quality Prediction with Physics-Guided Dual Neural ODEs in Open Systems
Jindong Tian, Yuxuan Liang, Ronghui Xu +6
Air pollution significantly threatens human health and ecosystems, necessitating effective air quality prediction to inform public policy. Traditional approaches are generally cate…
EasyTime: Time Series Forecasting Made Easy
Xiangfei Qiu, Xiuwen Li, Ruiyang Pang +11
Time series forecasting has important applications across diverse domains. EasyTime, the system we demonstrate, facilitates easy use of time-series forecasting methods by researche…