From the 1 of 9 linked papers with an AI index.
9 papers
LieBN: Batch Normalization over Lie Groups
Ziheng Chen, Yue Song, Rui Wang +2
The paper introduces LieBN, a batch‑normalization framework that works on data lying on Lie groups, providing theoretical control of Riemannian mean and variance across several com…
Towards Robust EEG Decoding Based on Riemannian Self-Attention
Shaocheng Jin, Tao Zhou, Rui Wang +4
Brain-Computer Interface (BCI) based on electroencephalography (EEG) enables direct interaction between the brain and external environments and has significant applications in assi…
Weierstrass Positional Encoding for Vision Transformers
Zhihang Xin, Rui Wang, Xitong Hu +1
Vision Transformers have achieved remarkable success in computer vision, but their common use of learnable one-dimensional positional encodings weakens the inherent two-dimensional…
Riemannian Networks over Full-Rank Correlation Matrices
Ziheng Chen, Xiaojun Wu, Bernhard Schölkopf +1
Representations on the Symmetric Positive Definite (SPD) manifold have garnered significant attention across different applications. In contrast, the manifold of full-rank correlat…
Fast and Stable Riemannian Metrics on SPD Manifolds via Cholesky Product Geometry
Ziheng Chen, Yue Song, Xiao-Jun Wu +1
Recent advances in Symmetric Positive Definite (SPD) matrix learning show that Riemannian metrics are fundamental to effective SPD neural networks. Motivated by this, we revisit th…
Wasserstein-Aligned Hyperbolic Multi-View Clustering
Rui Wang, Yuting Jiang, Xiaoqing Luo +3
Multi-view clustering (MVC) aims to uncover the latent structure of multi-view data by learning view-common and view-specific information. Although recent studies have explored hyp…