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Chang Tang

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Open access Sep 2026

Geo2DGS‐SLAM: Geometry‐Driven SLAM With 2D Gaussian Splatting

Recent advances in SLAM systems based on 3D Gaussian Splatting have enabled dense and photorealistic scene reconstruction. However, 3DGS‐based methods still suffer from limited geometric awareness due to the lack of normal rendering support, view inconsistency and weak depth constraints, ultimately hindering high‐f...

Wei-Qing Yan, Tian-Hao Xie, Liang Liao et al. · 0 citations
Conference Open access Sep 2026

Instance-Aligned Semantic Reconstruction for Incomplete Multi-View Clustering

IASR is proposed, an Instance-Aligned Semantic Reconstruction framework for IMVC that formulates missing-view recovery as a cross-view token alignment generator, and introduces a stable–active dual-encoder representation architecture with a generative-adaptive contrastive learning strategy that tightly couples view com...

Wei-Qing Yan, Yong-Teng Du, Peng Song et al. · 0 citations
Sep 2026

Hybrid Conditional Diffusion With Implicit Repair for Incomplete Multiview Clustering.

A two-stage framework, termed hybrid conditional diffusion with implicit repair for IMVC (HCDIR-IMVC), which simplifies the integration of diffusion models while improving the consistency and robustness of the recovered features and incorporates contrastive learning into the diffusion framework.

Wei-Qing Yan, Kang-Long Liu, Chang Tang et al. · 0 citations
Conference Open access Sep 2026

Spot-Adaptive Structural Rectification for Spatially Resolved Transcriptomics Data Clustering

A Spot-Adaptive Structural Rectification method that projects gene expression profiles onto a unit hypersphere to maximize angular distances, effectively separating spots falsely clustered by high total counts and surpasses state-of-the-art methods in spatial clustering.

Huan-Jia Zhao, Shang-Hui Deng, Shunfanyi Li et al. · 0 citations
Jul 2026

Hierarchical Graph Representation Learning From a Statistical Perspective for Generalizable and Interpretable Protein-Ligand Binding Affinity Prediction.

Protein-ligand binding affinity (PLA) prediction aims to guide rational drug design by estimating the strength of interaction. The effectiveness of the representation learning of protein and ligand is key to successful PLA prediction. To this end, attention mechanism, as a powerful architectural paradigm, has been intr...

Changming Yao, Shunfanyi Li, Shanghui Deng et al. · 0 citations

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