3 papers
cs.LG2026
Learning What Not to Impute: An Uncertainty-Aware Diffusion Framework for Meaningful Missingness
Lixing Zhang, Yidong Ouyang, Weifu Li +3
Missing value imputation is a fundamental task in machine learning, with most existing methods assuming that all missing entries correspond to unobserved regular values. In many re…
cs.CV2025
Clustering-Guided Multi-Layer Contrastive Representation Learning for Citrus Disease Classification
Jun Chen, Yonghua Yu, Weifu Li +2
Citrus, as one of the most economically important fruit crops globally, suffers severe yield depressions due to various diseases. Accurate disease detection and classification serv…
cs.CV2024
TSGaussian: Semantic and Depth-Guided Target-Specific Gaussian Splatting from Sparse Views
Liang Zhao, Zehan Bao, Yi Xie +3
Recent advances in Gaussian Splatting have significantly advanced the field, achieving both panoptic and interactive segmentation of 3D scenes. However, existing methodologies ofte…