19 citations · 23 across the 8 of their papers we have counts for
8 papers
CloudCons: A Comprehensive End-to-End Benchmark for Cloud Resource Consolidation
Xiaobin Zhang, Lefei Shen, Mouxiang Chen +6
Driven by conservative over-provisioning to guarantee service reliability, resource utilization in cloud data centers remains at low levels. To mitigate this, the forecast-then-opt…
TSFMAudit: Data Contamination Auditing in Forecasting Time Series Foundation Models
Hongkai Li, Shifeng Xie, Lefei Shen +7
Time series foundation models (TSFMs) are increasingly pretrained on large corpora, raising concerns that evaluation datasets may have been exposed during pretraining and thus yiel…
Skillful Kilometer-Scale Regional Weather Forecasting via Global and Regional Coupling
Weiqi Chen, Wenwei Wang, Qilong Yuan +5
Data-driven weather models have advanced global medium-range forecasting, yet high-resolution regional prediction remains challenging due to unresolved multiscale interactions betw…
VisionTS++: Cross-Modal Time Series Foundation Model with Continual Pre-trained Vision Backbones
Lefei Shen, Mouxiang Chen, Xu Liu +5
Recent studies have indicated that vision models pre-trained on images can serve as time series foundation models (TSFMs) by reformulating time series forecasting (TSF) as image re…
The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting
Lefei Shen, Mouxiang Chen, Han Fu +5
Transformer-based models have recently become dominant in Long-term Time Series Forecasting (LTSF), yet the variations in their architecture, such as encoder-only, encoder-decoder,…
Utilizing Strategic Pre-training to Reduce Overfitting: Baguan -- A Pre-trained Weather Forecasting Model
Peisong Niu, Ziqing Ma, Tian Zhou +4
Weather forecasting has long posed a significant challenge for humanity. While recent AI-based models have surpassed traditional numerical weather prediction (NWP) methods in globa…
VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters
Mouxiang Chen, Lefei Shen, Zhuo Li +3
Foundation models have emerged as a promising approach in time series forecasting (TSF). Existing approaches either repurpose large language models (LLMs) or build large-scale time…
Calibration of Time-Series Forecasting: Detecting and Adapting Context-Driven Distribution Shift
Mouxiang Chen, Lefei Shen, Han Fu +3
Recent years have witnessed the success of introducing deep learning models to time series forecasting. From a data generation perspective, we illustrate that existing models are s…