Variational hybridization and transformation for large inaccurate noisy-or networks. - Yusheng Xie; Nan Du 001; Wei Fan 001; Jing Zhai; Weicheng Zhu (CoRR, 2016)

Baidu Apollo EM Motion Planner. - Haoyang Fan; Fan Zhu; Changchun Liu; Liangliang Zhang; Li Zhuang; Dong Li; Weicheng Zhu; Jiangtao Hu; Hongye Li; Qi Kong (CoRR, 2018)

Graph Neural Network on Electronic Health Records for Predicting Alzheimer's Disease. - Weicheng Zhu; Narges Razavian (CoRR, 2019)

Variationally regularized graph-based representation learning for electronic health records. - Weicheng Zhu; Narges Razavian (CHIL, 2021)

Deep Probability Estimation. - Sheng Liu; Aakash Kaku; Weicheng Zhu; Matan Leibovich; Sreyas Mohan; Boyang Yu 003; Laure Zanna; Narges Razavian; Carlos Fernandez-Granda (CoRR, 2021)

Adaptive Early-Learning Correction for Segmentation from Noisy Annotations. - Sheng Liu; Kangning Liu; Weicheng Zhu; Yiqiu Shen; Carlos Fernandez-Granda (CVPR, 2022)

Deep Probability Estimation. - Sheng Liu; Aakash Kaku; Weicheng Zhu; Matan Leibovich; Sreyas Mohan; Boyang Yu 003; Haoxiang Huang; Laure Zanna; Narges Razavian; Jonathan Niles-Weed; Carlos Fernandez-Granda (ICML, 2022)

Interpretable Prediction of Lung Squamous Cell Carcinoma Recurrence With Self-supervised Learning. - Weicheng Zhu; Carlos Fernandez-Granda; Narges Razavian (MIDL, 2022)

Motion planning in complex urban environments: An industrial application on autonomous last-mile delivery vehicles. - Haiming Wang; Liangliang Zhang; Qi Kong; Weicheng Zhu; Jie Zheng; Li Zhuang; Xin Xu (J. Field Robotics, 2022)

Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning. - Kangning Liu; Weicheng Zhu; Yiqiu Shen; Sheng Liu; Narges Razavian; Krzysztof J. Geras; Carlos Fernandez-Granda (CVPR, 2023)

A Monte Carlo Framework for Calibrated Uncertainty Estimation in Sequence Prediction. - Qidong Yang; Weicheng Zhu; Joseph Keslin; Laure Zanna; Tim G. J. Rudner; Carlos Fernandez-Granda (CoRR, 2024)

Making Self-supervised Learning Robust to Spurious Correlation via Learning-speed Aware Sampling. - Weicheng Zhu; Sheng Liu; Carlos Fernandez-Granda; Narges Razavian (Trans. Mach. Learn. Res., 2025)

3D Foundation AI Model for Generalizable Disease Detection in Head Computed Tomography. - Weicheng Zhu; Haoxu Huang; Huanze Tang; Rushabh Musthyala; Boyang Yu 003; Long Chen; Emilio Vega; Thomas O'Donnell; Seena Dehkharghani; Jennifer A. Frontera; Arjun V. Masurkar; Kara Melmed; et al. (CoRR, 2025)

Foundation Models for Clinical Records at Health System Scale. - Haresh Rengaraj Rajamohan; Xiang Gao; Weicheng Zhu; Shih-Lun Huang; Long Chen; Kyunghyun Cho; Cem M. Deniz; Narges Razavian (CoRR, 2025)