Deep Grouping Model for Unified Perceptual Parsing. - Zhiheng Li 002; Wenxuan Bao; Jiayang Zheng; Chenliang Xu (CVPR, 2020)

On the Importance of Architecture and Feature Selection in Differentially Private Machine Learning. - Wenxuan Bao; Luke A. Bauer; Vincent Bindschaedler (CoRR, 2022)

BOBA: Byzantine-Robust Federated Learning with Label Skewness. - Wenxuan Bao; Jingrui He (CoRR, 2022)

High-Precision Population Spatialization in Metropolises Based on Ensemble Learning: A Case Study of Beijing, China. - Wenxuan Bao; Adu Gong; Yiran Zhao; Shuaiqiang Chen; Wanru Ba; Yuan He 013 (Remote. Sens., 2022)

A Zoning Earthquake Casualty Prediction Model Based on Machine Learning. - Boyi Li; Adu Gong; Tingting Zeng; Wenxuan Bao; Can Xu; Zhiqing Huang (Remote. Sens., 2022)

Optimizing the Collaboration Structure in Cross-Silo Federated Learning. - Wenxuan Bao; Haohan Wang; Jun Wu 019; Jingrui He (ICML, 2023)

Personalized Federated Learning with Parameter Propagation. - Jun Wu 019; Wenxuan Bao; Elizabeth A. Ainsworth; Jingrui He (KDD, 2023)

DP-Mix: Mixup-based Data Augmentation for Differentially Private Learning. - Wenxuan Bao; Francesco Pittaluga; Vijay Kumar B. G; Vincent Bindschaedler (NeurIPS, 2023)

Adaptive Test-Time Personalization for Federated Learning. - Wenxuan Bao; Tianxin Wei; Haohan Wang; Jingrui He (NeurIPS, 2023)

Understanding the Effect of Data Augmentation on Knowledge Distillation. - Ziqi Wang 003; Chi Han; Wenxuan Bao; Heng Ji 001 (CoRR, 2023)

Privacy-Preserving Graph Machine Learning from Data to Computation: A Survey. - Dongqi Fu; Wenxuan Bao; Ross Maciejewski; Hanghang Tong; Jingrui He (SIGKDD Explor., 2023)

Mapping Population Distribution with High Spatiotemporal Resolution in Beijing Using Baidu Heat Map Data. - Wenxuan Bao; Adu Gong; Tong Zhang; Yiran Zhao; Boyi Li; Shuaiqiang Chen (Remote. Sens., 2023)

Urban Tree Canopy Mapping Based on Double-Branch Convolutional Neural Network and Multi-Temporal High Spatial Resolution Satellite Imagery. - Shuaiqiang Chen; Meng Chen; Bingyu Zhao; Ting Mao; Jianjun Wu 001; Wenxuan Bao (Remote. Sens., 2023)

An Object-Oriented Method for Extracting Single-Object Aquaculture Ponds from 10 m Resolution Sentinel-2 Images on Google Earth Engine. - Boyi Li; Adu Gong; Zikun Chen; Xiang Pan; Lingling Li; Jinglin Li; Wenxuan Bao (Remote. Sens., 2023)

A peer-to-peer file storage and sharing system based on consortium blockchain. - Shaoliang Peng; Wenxuan Bao; Hao Liu; Xia Xiao; Jiandong Shang; Lin Han; Shan Wang; Xiaolan Xie; Yang Xu (Future Gener. Comput. Syst., 2023)

R+R: Towards Reliable and Generalizable Differentially Private Machine Learning. - Wenxuan Bao; Vincent Bindschaedler (ACSAC, 2024)

BOBA: Byzantine-Robust Federated Learning with Label Skewness. - Wenxuan Bao; Jun Wu 019; Jingrui He (AISTATS, 2024)

FedSelect: Personalized Federated Learning with Customized Selection of Parameters for Fine-Tuning. - Rishub Tamirisa; Chulin Xie; Wenxuan Bao; Andy Zhou; Ron Arel; Aviv Shamsian (CVPR, 2024)

AdaRC: Mitigating Graph Structure Shifts during Test-Time. - Wenxuan Bao; Zhichen Zeng 001; Zhining Liu 002; Hanghang Tong; Jingrui He (CoRR, 2024)

Matcha: Mitigating Graph Structure Shifts with Test-Time Adaptation. - Wenxuan Bao; Zhichen Zeng 001; Zhining Liu 002; Hanghang Tong; Jingrui He (ICLR, 2025)

Ask, and it shall be given: On the Turing completeness of prompting. - Ruizhong Qiu; Zhe Xu 007; Wenxuan Bao; Hanghang Tong (ICLR, 2025)

Connecting Domains and Contrasting Samples: A Ladder for Domain Generalization. - Tianxin Wei; Yifan Chen 004; Xinrui He; Wenxuan Bao; Jingrui He (KDD (1), 2025)

Provably Secure Covert Messaging Using Image-Based Diffusion Processes. - Luke A. Bauer; Wenxuan Bao; Vincent Bindschaedler (SaTML, 2025)

Inference Attacks for X-Vector Speaker Anonymization. - Luke A. Bauer; Wenxuan Bao; Malvika Jadhav; Vincent Bindschaedler (SP (Workshops), 2025)

Pave Your Own Path: Graph Gradual Domain Adaptation on Fused Gromov-Wasserstein Geodesics. - Zhichen Zeng 001; Ruizhong Qiu; Wenxuan Bao; Tianxin Wei; Xiao Lin; Yuchen Yan; Tarek F. Abdelzaher; Jiawei Han 001; Hanghang Tong (CoRR, 2025)

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning. - Wenxuan Bao; Ruxi Deng; Ruizhong Qiu; Tianxin Wei; Hanghang Tong; Jingrui He (CoRR, 2025)

Thwart Me If You Can: An Empirical Analysis of Android Platform Armoring Against Stalkerware. - Malvika Jadhav; Wenxuan Bao; Vincent Bindschaedler (CoRR, 2025)

Towards Reliable and Generalizable Differentially Private Machine Learning (Extended Version). - Wenxuan Bao; Vincent Bindschaedler (CoRR, 2025)