From the 1 of 31 linked papers with an AI index.
1 citations · 1 across the 9 of their papers we have counts for
29 papers · 1 filter
Enhancing Irregular Time Series Forecasting with Continuous-Time Modeling Framework
Tianen Shen, Zhengyu Li, Yutong Li +4
The paper introduces WrapFlow, a framework that directly tokenizes irregular multivariate time‑series observations into continuous‑time tokens and uses a Transformer with a simulat…
UniWind: Toward Unified Day-Ahead Wind Power Forecasting via Physics-Informed State Routing
Ronghui Xu, Tongxin Wu, Guozhen Zhang +4
Day-ahead wind power forecasting is essential for cost-effective power-system operation. It is primarily driven by future meteorological conditions while retaining temporal depende…
CATCH: Channel-Aware multivariate Time Series Anomaly Detection via Frequency Patching
Xingjian Wu, Xiangfei Qiu, Zhengyu Li +5
Anomaly detection in multivariate time series is challenging as heterogeneous subsequence anomalies may occur. Reconstruction-based methods, which focus on learning normal patterns…
Differentiable Mixture-of-Agents Incentivizes Swarm Intelligence of Large Language Models
Xingjian Wu, Junkai Lu, Siyu Yan +4
Recent advances in Large Language Models (LLMs) have catalyzed the development of multi-agent systems (MAS) for complex reasoning tasks. However, existing MAS typically rely on pre…
DAG: A Dual Correlation Network for Time Series Forecasting with Exogenous Variables
Xiangfei Qiu, Yuhan Zhu, Zhengyu Li +3
Time series forecasting is essential in various domains. Compared to relying solely on endogenous variables (i.e., target variables), considering exogenous variables (i.e., covaria…
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…