12 papers
Self-Gating Attention for Efficient Time Series Forecasting
Dezheng Wang, Tong Chen, Wei Yuan +3
Transformer architectures have shown strong potential in time series forecasting, where multi-head self-attention is widely used to capture temporal dependencies across historical…
A Systematic Survey and Benchmark of Deep Learning for Molecular Property Prediction in the Foundation Model Era
Zongru Li, Xingsheng Chen, Honggang Wen +8
Molecular property prediction integrates quantum chemistry, cheminformatics, and deep learning to connect molecular structure with physicochemical and biological behavior. This sur…
Time Series Analysis in Frequency Domain: A Survey of Open Challenges, Opportunities and Benchmarks
Qianru Zhang, Yuting Sun, Honggang Wen +6
Frequency-domain analysis has emerged as a powerful paradigm for time series analysis, offering unique advantages over traditional time-domain approaches while introducing new theo…
HGAurban: Heterogeneous Graph Autoencoding for Urban Spatial-Temporal Learning
Qianru Zhang, Xinyi Gao, Haixin Wang +3
Spatial-temporal graph representations play a crucial role in urban sensing applications, including traffic analysis, human mobility behavior modeling, and citywide crime predictio…
Watermarking Large Language Model-based Time Series Forecasting
Wei Yuan, Chaoqun Yang, Yu Xing +3
Large Language Model-based Time Series Forecasting (LLMTS) has shown remarkable promise in handling complex and diverse temporal data, representing a significant step toward founda…
FLDmamba: Integrating Fourier and Laplace Transform Decomposition with Mamba for Enhanced Time Series Prediction
Qianru Zhang, Chenglei Yu, Haixin Wang +5
Time series prediction, a crucial task across various domains, faces significant challenges due to the inherent complexities of time series data, including non-stationarity, multi-…