199 citations · 203 across the 10 of their papers we have counts for
5 papers · 1 filter
T-LLM: Teaching Large Language Models to Forecast Time Series via Temporal Distillation
Suhan Guo, Bingxu Wang, Shaodan Zhang +1
Time series forecasting plays a critical role in decision-making across many real-world applications. Unlike data in vision and language domains, time series data is inherently tie…
Enhancing Epidemic Forecasting: Evaluating the Role of Mobility Data and Graph Convolutional Networks
Suhan Guo, Zhenghao Xu, Furao Shen +1
Accurate prediction of contagious disease outbreaks is vital for informed decision-making. Our study addresses the gap between machine learning algorithms and their epidemiological…
SPAT: Sensitivity-based Multihead-attention Pruning on Time Series Forecasting Models
Suhan Guo, Jiahong Deng, Mengjun Yi +2
Attention-based architectures have achieved superior performance in multivariate time series forecasting but are computationally expensive. Techniques such as patching and adaptive…
RAM: Replace Attention with MLP for Efficient Multivariate Time Series Forecasting
Suhan Guo, Jiahong Deng, Yi Wei +3
Attention-based architectures have become ubiquitous in time series forecasting tasks, including spatio-temporal (STF) and long-term time series forecasting (LTSF). Yet, our unders…
Multi-Scale Dilated Convolution Network for Long-Term Time Series Forecasting
Feifei Li, Suhan Guo, Feng Han +2
Accurate forecasting of long-term time series has important applications for decision making and planning. However, it remains challenging to capture the long-term dependencies in…