Towards efficient load distribution in big data cloud. - Zhi Liu; Xiang Wang; Weishen Pan; Baohua Yang; Xiaohe Hu; Jun Li 003 (ICNC, 2015)

A Style Transformation Method for Printed Chinese Characters. - Huiyun Mao; Weishen Pan (ICIG (1), 2015)

Automatic Methods for Screening and Assessing Scoliosis by 2-D Digital Images. - Weishen Pan; Guangdong Hou; Changshui Zhang (IScIDE (1), 2015)

SpottingNet: Learning the Similarity of Word Images with Convolutional Neural Network for Word Spotting in Handwritten Historical Documents. - Zhuoyao Zhong; Weishen Pan; Lianwen Jin; Harold Mouchère; Christian Viard-Gaudin (ICFHR, 2016)

Weakly- and Semi-Supervised Object Detection with Expectation-Maximization Algorithm. - Ziang Yan; Jian Liang 002; Weishen Pan; Jin Li 020; Changshui Zhang (CoRR, 2017)

xOrder: A Model Agnostic Post-Processing Framework for Achieving Ranking Fairness While Maintaining Algorithm Utility. - Sen Cui; Weishen Pan; Changshui Zhang; Fei Wang 001 (CoRR, 2020)

Deep Gesture Video Generation With Learning on Regions of Interest. - Runpeng Cui; Zhong Cao; Weishen Pan; Changshui Zhang; Jianqiang Wang 003 (IEEE Trans. Multim., 2020)

Towards Model-Agnostic Post-Hoc Adjustment for Balancing Ranking Fairness and Algorithm Utility. - Sen Cui; Weishen Pan; Changshui Zhang; Fei Wang 001 (KDD, 2021)

Explaining Algorithmic Fairness Through Fairness-Aware Causal Path Decomposition. - Weishen Pan; Sen Cui; Jiang Bian 001; Changshui Zhang; Fei Wang 001 (KDD, 2021)

Addressing Algorithmic Disparity and Performance Inconsistency in Federated Learning. - Sen Cui; Weishen Pan; Jian Liang 002; Changshui Zhang; Fei Wang 001 (NeurIPS, 2021)

The Definitions of Interpretability and Learning of Interpretable Models. - Weishen Pan; Changshui Zhang (CoRR, 2021)

Learning to Collaborate. - Sen Cui; Jian Liang 002; Weishen Pan; Kun Chen 002; Changshui Zhang; Fei Wang 001 (CoRR, 2021)

Fair and Consistent Federated Learning. - Sen Cui; Weishen Pan; Jian Liang 002; Changshui Zhang; Fei Wang 001 (CoRR, 2021)

Correcting the User Feedback-Loop Bias for Recommendation Systems. - Weishen Pan; Sen Cui; Hongyi Wen; Kun Chen 002; Changshui Zhang; Fei Wang 001 (CoRR, 2021)

Collaboration Equilibrium in Federated Learning. - Sen Cui; Jian Liang 002; Weishen Pan; Kun Chen 002; Changshui Zhang; Fei Wang 001 (KDD, 2022)

InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models. - Yingheng Wang; Yair Schiff; Aaron Gokaslan; Weishen Pan; Fei Wang 001; Christopher De Sa; Volodymyr Kuleshov (ICML, 2023)

Mining Electronic Health Records for Real-World Evidence. - Chengxi Zang; Weishen Pan; Fei Wang 001 (KDD, 2023)

Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources. - Suraj Rajendran; Weishen Pan; Mert R. Sabuncu; Yong Chen 016; Jiayu Zhou; Fei Wang 001 (CoRR, 2023)

Bipartite Ranking Fairness Through a Model Agnostic Ordering Adjustment. - Sen Cui; Weishen Pan; Changshui Zhang; Fei Wang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

CLAP: Collaborative Adaptation for Patchwork Learning. - Sen Cui; Abudukelimu Wuerkaixi; Weishen Pan; Jian Liang 002; Lei Fang; Changshui Zhang; Fei Wang 001 (ICLR, 2024)

Unified Insights: Harnessing Multi-modal Data for Phenotype Imputation via View Decoupling. - Qiannan Zhang; Weishen Pan; Zilong Bai; Chang Su; Fei Wang (NeurIPS, 2024)

Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs. - Jacqueline R. M. A. Maasch; Weishen Pan; Shantanu Gupta; Volodymyr Kuleshov; Kyra Gan; Fei Wang 001 (UAI, 2024)

Joint Analysis of Single-Cell Data across Cohorts with Missing Modalities. - Marianne Arriola; Weishen Pan; Manqi Zhou; Qiannan Zhang; Chang Su; Fei Wang (CoRR, 2024)

Augmented Risk Prediction for the Onset of Alzheimer's Disease from Electronic Health Records with Large Language Models. - Jiankun Wang 002; Sumyeong Ahn; Taykhoom Dalal; Xiaodan Zhang; Weishen Pan; Qiannan Zhang; Bin Chen; Hiroko H. Dodge; Fei Wang; Jiayu Zhou (CoRR, 2024)

Learning across diverse biomedical data modalities and cohorts: Challenges and opportunities for innovation. - Suraj Rajendran; Weishen Pan; Mert R. Sabuncu; Yong Chen 016; Jiayu Zhou; Fei Wang 001 (Patterns, 2024)

An adaptive federated learning framework for clinical risk prediction with electronic health records from multiple hospitals. - Weishen Pan; Zhenxing Xu; Suraj Rajendran; Fei Wang 001 (Patterns, 2024)

Federated target trial emulation using distributed observational data for treatment effect estimation. - Haoyang Li 001; Chengxi Zang; Zhenxing Xu; Weishen Pan; Suraj Rajendran; Yong Chen 016; Fei Wang 001 (npj Digit. Medicine, 2025)

MOSIC: Model-Agnostic Optimal Subgroup Identification with Multi-Constraint for Improved Reliability. - Wenxin Chen; Weishen Pan; Kyra Gan; Fei Wang 001 (CoRR, 2025)