7 papers
Structured Latent Space Modeling over Multi-Scale Temporal Patches for Multivariate Time Series Forecasting
Xingsheng Chen, Deyu Yi, Siu-Ming Yiu
Existing patching and multi-scale methods advance multivariate time series forecasting but treat learned representations as transient byproducts of prediction, lacking explicit mec…
UniMamba: A Unified Spatial-Temporal Modeling Framework with State-Space and Attention Integration
Xingsheng Chen, Xianpei Mu, Deyu Yi +6
Multivariate time series forecasting is fundamental to numerous domains such as energy, finance, and environmental monitoring, where complex temporal dependencies and cross-variabl…
SPDM: Geometry-Modulated State Space Modeling with Manifold Constraints for Time Series Forecasting
Xingsheng Chen, Siu-Ming Yiu
Multivariate time series forecasting requires capturing the continuously evolving correlation structure among interacting variables. Existing state-space models process time series…
DFIR-DETR: Frequency-Domain Iterative Refinement and Dynamic Feature Aggregation for Small Object Detection
Bo Gao, Jingcheng Tong, Xingsheng Chen +2
Small object detection in complex scenes exposes a fundamental tension in neural network design: backbone attention distributes computation uniformly regardless of content, pyramid…
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…
MODE: Efficient Time Series Prediction with Mamba Enhanced by Low-Rank Neural ODEs
Xingsheng Chen, Regina Zhang, Bo Gao +5
Time series prediction plays a pivotal role across diverse domains such as finance, healthcare, energy systems, and environmental modeling. However, existing approaches often strug…