37 citations · 43 across the 24 of their papers we have counts for
10 papers · 1 filter
Towards Non-Stationary Time Series Forecasting with Temporal Stabilization and Frequency Differencing
Junkai Lu, Peng Chen, Chenjuan Guo +3
Time series forecasting is critical for decision-making across dynamic domains such as energy, finance, transportation, and cloud computing. However, real-world time series often e…
STAR: Boosting Time Series Foundation Models for Anomaly Detection through State-aware Adapter
Hanyin Cheng, Ruitong Zhang, Yuning Lu +5
While Time Series Foundation Models (TSFMs) have demonstrated remarkable success in Multivariate Time Series Anomaly Detection (MTSAD), however, in real-world industrial scenarios,…
CrossAD: Time Series Anomaly Detection with Cross-scale Associations and Cross-window Modeling
Beibu Li, Qichao Shentu, Yang Shu +5
Time series anomaly detection plays a crucial role in a wide range of real-world applications. Given that time series data can exhibit different patterns at different sampling gran…
CC-Time: Cross-Model and Cross-Modality Time Series Forecasting
Peng Chen, Yihang Wang, Yang Shu +6
With the success of pre-trained language models (PLMs) in various application fields beyond natural language processing, language models have raised emerging attention in the field…
Aurora: Towards Universal Generative Multimodal Time Series Forecasting
Xingjian Wu, Jianxin Jin, Wanghui Qiu +4
Cross-domain generalization is very important in Time Series Forecasting because similar historical information may lead to distinct future trends due to the domain-specific charac…
Towards Measuring and Modeling Geometric Structures in Time Series Forecasting via Image Modality
Mingyang Yu, Xiahui Guo, Peng chen +2
Time Series forecasting is critical in diverse domains such as weather forecasting, financial investment, and traffic management. While traditional numerical metrics like mean squa…
LightGTS: A Lightweight General Time Series Forecasting Model
Yihang Wang, Yuying Qiu, Peng Chen +5
Existing works on general time series forecasting build foundation models with heavy model parameters through large-scale multi-source pre-training. These models achieve superior g…
AimTS: Augmented Series and Image Contrastive Learning for Time Series Classification
Yuxuan Chen, Shanshan Huang, Yunyao Cheng +6
Time series classification (TSC) is an important task in time series analysis. Existing TSC methods mainly train on each single domain separately, suffering from a degradation in a…
Learning Generalizable Skills from Offline Multi-Task Data for Multi-Agent Cooperation
Sicong Liu, Yang Shu, Chenjuan Guo +1
Learning cooperative multi-agent policy from offline multi-task data that can generalize to unseen tasks with varying numbers of agents and targets is an attractive problem in many…
RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems
Biao Ouyang, Yingying Zhang, Hanyin Cheng +6
With the continued migration of storage to cloud database systems,the impact of slow queries in such systems on services and user experience is increasing. Root-cause diagnosis pla…