4 papers · 1 filter
We Need a More Robust Classifier: Dual Causal Learning Empowers Domain-Incremental Time Series Classification
Zhipeng Liu, Peibo Duan, Xuan Tang +6
The World Wide Web thrives on intelligent services that rely on accurate time series classification, which has recently witnessed significant progress driven by advances in deep le…
Gated Fusion Enhanced Multi-Scale Hierarchical Graph Convolutional Network for Stock Movement Prediction
Xiaosha Xue, Peibo Duan, Zhipeng Liu +3
Accurately predicting stock market movements remains a formidable challenge due to the inherent volatility and complex interdependencies among stocks. Although multi-scale Graph Ne…
TimeFormer: Transformer with Attention Modulation Empowered by Temporal Characteristics for Time Series Forecasting
Zhipeng Liu, Peibo Duan, Xuan Tang +6
Although Transformers excel in natural language processing, their extension to time series forecasting remains challenging due to insufficient consideration of the differences betw…
A Distillation-based Future-aware Graph Neural Network for Stock Trend Prediction
Zhipeng Liu, Peibo Duan, Mingyang Geng +1
Stock trend prediction involves forecasting the future price movements by analyzing historical data and various market indicators. With the advancement of machine learning, graph n…