2 citations · 6 across the 13 of their papers we have counts for
12 papers · 1 filter
WorldTS: World Modeling for Multimodal Covariate-aware Time Series Forecasting
Yuhan Zhu, Xiangfei Qiu, Hanyin Cheng +5
Time series forecasting is typically framed as learning a direct mapping from historical to future observations in the observation space. However, sequences of observations general…
TimeBlocks: Foundational and Continual Time-Series Blockbase -- Extended Version
David Campos, Bin Yang, Tung Kieu +3
The ongoing digitization has led to a proliferation of time-series data streams that monitor a variety of processes, from which valuable insights may be obtained. Further, the emer…
DiSGMM: A Method for Time-varying Microscopic Weight Completion on Road Networks
Yan Lin, Jilin Hu, Shengnan Guo +3
Microscopic road-network weights represent fine-grained, time-varying traffic conditions obtained from individual vehicles. An example is travel speeds associated with road segment…
TimeART: Towards Agentic Time Series Reasoning via Tool-Augmentation
Xingjian Wu, Junkai Lu, Zhengyu Li +5
Time series data widely exist in real-world cyber-physical systems. Though analyzing and interpreting them contributes to significant values, e.g, disaster prediction and financial…
Hermes: A Multi-Scale Spatial-Temporal Hypergraph Network for Stock Time Series Forecasting
Xiangfei Qiu, Liu Yang, Xiangyu Xu +9
Time series forecasting occurs in a range of financial applications providing essential decision-making support to investors, regulatory institutions, and analysts. Unlike multivar…
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…
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…
Fully Automated Correlated Time Series Forecasting in Minutes
Xinle Wu, Xingjian Wu, Dalin Zhang +4
Societal and industrial infrastructures and systems increasingly leverage sensors that emit correlated time series. Forecasting of future values of such time series based on record…
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…
TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods
Xiangfei Qiu, Jilin Hu, Lekui Zhou +8
Time series are generated in diverse domains such as economic, traffic, health, and energy, where forecasting of future values has numerous important applications. Not surprisingly…
UVTM: Universal Vehicle Trajectory Modeling with ST Feature Domain Generation
Yan Lin, Jilin Hu, Shengnan Guo +4
Vehicle movement is frequently captured in the form of GPS trajectories, i.e., sequences of timestamped GPS locations. Such data is widely used for various tasks such as travel-tim…
Learning Time-aware Graph Structures for Spatially Correlated Time Series Forecasting
Minbo Ma, Jilin Hu, Christian S. Jensen +4
Spatio-temporal forecasting of future values of spatially correlated time series is important across many cyber-physical systems (CPS). Recent studies offer evidence that the use o…