1 code implementation • 20 Jul 2020 • Hanqing Chao, Xi Fang, Jiajin Zhang, Fatemeh Homayounieh, Chiara D. Arru, Subba R. Digumarthy, Rosa Babaei, Hadi K. Mobin, Iman Mohseni, Luca Saba, Alessandro Carriero, Zeno Falaschi, Alessio Pasche, Ge Wang, Mannudeep K. Kalra, Pingkun Yan
Management of high-risk patients with early intervention is a key to lower the fatality rate of COVID-19 pneumonia, as a majority of patients recover naturally.
1 code implementation • 3 Nov 2020 • Bochao Wang, Hang Xu, Jiajin Zhang, Chen Chen, Xiaozhi Fang, Yixing Xu, Ning Kang, Lanqing Hong, Chenhan Jiang, Xinyue Cai, Jiawei Li, Fengwei Zhou, Yong Li, Zhicheng Liu, Xinghao Chen, Kai Han, Han Shu, Dehua Song, Yunhe Wang, Wei zhang, Chunjing Xu, Zhenguo Li, Wenzhi Liu, Tong Zhang
Automated Machine Learning (AutoML) is an important industrial solution for automatic discovery and deployment of the machine learning models.
no code implementations • 18 Nov 2020 • Jiajin Zhang, Hanqing Chao, Pingkun Yan
Unsupervised domain adaptation (UDA) is widely used to transfer knowledge from a labeled source domain to an unlabeled target domain with different data distribution.
1 code implementation • 25 Mar 2021 • Jiajin Zhang, Hanqing Chao, Xuanang Xu, Chuang Niu, Ge Wang, Pingkun Yan
The extensive use of medical CT has raised a public concern over the radiation dose to the patient.
1 code implementation • 12 Jul 2022 • Hanqing Chao, Jiajin Zhang, Pingkun Yan
Regression plays an essential role in many medical imaging applications for estimating various clinical risk or measurement scores.
1 code implementation • 1 Dec 2022 • Jiajin Zhang, Hanqing Chao, Amit Dhurandhar, Pin-Yu Chen, Ali Tajer, Yangyang Xu, Pingkun Yan
Domain generalization (DG) aims to train a model to perform well in unseen domains under different distributions.
1 code implementation • 2 Feb 2023 • Junbo Zhao, Xuefei Ning, Enshu Liu, Binxin Ru, Zixuan Zhou, Tianchen Zhao, Chen Chen, Jiajin Zhang, Qingmin Liao, Yu Wang
In the first step, we train different sub-predictors on different types of available low-fidelity information to extract beneficial knowledge as low-fidelity experts.
1 code implementation • 3 Sep 2023 • Jiajin Zhang, Hanqing Chao, Amit Dhurandhar, Pin-Yu Chen, Ali Tajer, Yangyang Xu, Pingkun Yan
To accomplish this challenging task, first, a spectral sensitivity map is introduced to characterize the generalization weaknesses of models in the frequency domain.