4 papers
HFMCA: Orthonormal Feature Learning for EEG-based Brain Decoding
Yinghao Wang, Lintao Xu, Shujian Yu +2
Electroencephalography (EEG) analysis is critical for brain-computer interfaces and neuroscience, but the intrinsic noise and high dimensionality of EEG signals hinder effective fe…
Explainable Multimodal Regression via Information Decomposition
Zhaozhao Ma, Shujian Yu
Multimodal regression aims to predict a continuous target from heterogeneous input sources and typically relies on fusion strategies such as early or late fusion. However, existing…
InfoDPCCA: Information-Theoretic Dynamic Probabilistic Canonical Correlation Analysis
Shiqin Tang, Shujian Yu
Extracting meaningful latent representations from high-dimensional sequential data is a crucial challenge in machine learning, with applications spanning natural science and engine…
Deep Dynamic Probabilistic Canonical Correlation Analysis
Shiqin Tang, Shujian Yu, Yining Dong +1
This paper presents Deep Dynamic Probabilistic Canonical Correlation Analysis (D2PCCA), a model that integrates deep learning with probabilistic modeling to analyze nonlinear dynam…