Weicheng Zhu

发表

Deep Probability Estimation

N. Razavian, L. Zanna, C. Fernandez-Granda, 2021, ICML.

Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning

Krzysztof J. Geras, Krzysztof J Geras, N. Razavian, 2022, ArXiv.

Generalizable deep learning model for early Alzheimer’s disease detection from structural MRIs

N. Razavian, H. Rusinek, A. Masurkar, 2022, Scientific Reports.

Development of a Deep Learning Model for Early Alzheime's Disease Detection from Structural MRIs and External Validation on an Independent Cohort

N. Razavian, H. Rusinek, A. Masurkar, 2021, medRxiv.

Interpretable Prediction of Lung Squamous Cell Carcinoma Recurrence With Self-supervised Learning

N. Razavian, C. Fernandez-Granda, Weicheng Zhu, 2022, MIDL.

Variationally regularized graph-based representation learning for electronic health records

N. Razavian, Weicheng Zhu, 2019, CHIL.

Adaptive Early-Learning Correction for Segmentation from Noisy Annotations

Yiqiu Shen, C. Fernandez-Granda, Kangning Liu, 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Graph Neural Network on Electronic Health Records for Predicting Alzheimer's Disease pdf

Narges Razavian, Weicheng Zhu, N. Razavian, 2019, ArXiv.

Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning

Krzysztof J. Geras, N. Razavian, Yiqiu Shen, 2022, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Making Self-supervised Learning Robust to Spurious Correlation via Learning-speed Aware Sampling

N. Razavian, Weicheng Zhu, C. Fernandez‐Granda, 2023, ArXiv.

Identification of patients at risk for pancreatic cancer in a 3-year timeframe based on machine learning algorithms

N. Razavian, T. Gonda, F. Kastrinos, 2023, medRxiv.