6 papers
CRT*: Conditional Randomization Testing with Heterogeneous External and Unlabeled Data
Yingjie Zhang, Ziqi Chen, Chenlei Leng
The conditional randomization test (CRT) provides a principled approach to conditional independence (CI) testing, guaranteeing exact type-I error control when the true conditional…
Conditionally Whitened Generative Models for Probabilistic Time Series Forecasting
Yanfeng Yang, Siwei Chen, Pingping Hu +6
Probabilistic forecasting of multivariate time series is challenging due to non-stationarity, inter-variable dependencies, and distribution shifts. While recent diffusion and flow…
Uni-AIMS: AI-Powered Microscopy Image Analysis
Yanhui Hong, Nan Wang, Zhiyi Xia +11
This paper presents a systematic solution for the intelligent recognition and automatic analysis of microscopy images. We developed a data engine that generates high-quality annota…
Unleashing Diffusion and State Space Models for Medical Image Segmentation
Rong Wu, Ziqi Chen, Liming Zhong +2
Existing segmentation models trained on a single medical imaging dataset often lack robustness when encountering unseen organs or tumors. Developing a robust model capable of ident…
Nonlinear Sparse Generalized Canonical Correlation Analysis for Multi-view High-dimensional Data
Rong Wu, Ziqi Chen, Gen Li +1
Motivation: Biomedical studies increasingly produce multi-view high-dimensional datasets (e.g., multi-omics) that demand integrative analysis. Existing canonical correlation analys…
Conditional Diffusion Models Based Conditional Independence Testing
Yanfeng Yang, Shuai Li, Yingjie Zhang +4
Conditional independence (CI) testing is a fundamental task in modern statistics and machine learning. The conditional randomization test (CRT) was recently introduced to test whet…