6 papers
Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis
Yisong Fu, Zezhi Shao, Chengqing Yu +4
We present Zeus, a unified tuning-free Time Series Foundation Model (TSFM) that delivers superior performance across diverse analysis tasks without any task-specific fine-tuning. U…
A Nationwide Benchmark for Wildfire Initial Attack Failure Prediction with Public Environmental Data
Runyang Xu, Xueqi Cheng, Yushun Dong
Initial attack (IA) is the first wildfire suppression phase, when agencies must quickly decide which fires may escape early control. Existing IA failure prediction studies often us…
ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting
Fei Wang, Yujie Li, Zezhi Shao +5
Recent advancements in deep learning models for time series forecasting have been significant. These models often leverage fundamental time series properties such as seasonality an…
Segmenting Action-Value Functions Over Time-Scales in SARSA via TD()
Mahammad Humayoo
In numerous episodic reinforcement learning (RL) environments, SARSA-based methodologies are employed to enhance policies aimed at maximizing returns over long horizons. Traditiona…
BLAST: Balanced Sampling Time Series Corpus for Universal Forecasting Models
Zezhi Shao, Yujie Li, Fei Wang +7
The advent of universal time series forecasting models has revolutionized zero-shot forecasting across diverse domains, yet the critical role of data diversity in training these mo…
Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis
Zezhi Shao, Fei Wang, Yongjun Xu +10
Multivariate Time Series (MTS) analysis is crucial to understanding and managing complex systems, such as traffic and energy systems, and a variety of approaches to MTS forecasting…