Spatio-Temporal Similarity Measure based Multi-Task Learning for Predicting Alzheimer's Disease Progression using MRI Data

no code implementations • 6 Nov 2023 • Xulong Wang, Yu Zhang, Menghui Zhou, Tong Liu, Jun Qi, Po Yang

The experimental results show that compared with directly ROI based learning, our proposed method is more effective in predicting disease progression.

Multi-Task Learning

VDN-NeRF: Resolving Shape-Radiance Ambiguity via View-Dependence Normalization

1 code implementation • CVPR 2023 • Bingfan Zhu, Yanchao Yang, Xulong Wang, Youyi Zheng, Leonidas Guibas

We propose VDN-NeRF, a method to train neural radiance fields (NeRFs) for better geometry under non-Lambertian surface and dynamic lighting conditions that cause significant variation in the radiance of a point when viewed from different angles.

MFL_COVID19: Quantifying Country-based Factors affecting Case Fatality Rate in Early Phase of COVID-19 Epidemic via Regularised Multi-task Feature Learning

no code implementations • 6 Sep 2020 • Po Yang, Jun Qi, Xulong Wang, Yun Yang

The fused sparse group Lasso (FSGL) method allows the simultaneous selection of a common set of country-based factors for multiple time points of COVID-19 epidemic and also enables incorporating temporal smoothness of each factor over the whole early phase period.

feature selection Multi-Task Learning +1