1 code implementation • 8 Aug 2023 • Zitan Chen, Zhuang Qi, Xiao Cao, Xiangxian Li, Xiangxu Meng, Lei Meng
Representation learning for images has been advanced by recent progress in more complex neural models such as the Vision Transformers and new learning theories such as the structural causal models.
1 code implementation • 7 Aug 2023 • Zhuang Qi, Lei Meng, Zitan Chen, Han Hu, Hui Lin, Xiangxu Meng
To address this issue, this paper presents a cross-silo prototypical calibration method (FedCSPC), which takes additional prototype information from the clients to learn a unified feature space on the server side.
no code implementations • 8 May 2023 • Wei Li, Xiangxu Meng, Chuhao Chen, Jianing Chen
In this paper, we carefully examine the opposing properties of CI and CD, and raise a practical question that has not been effectively answered, e. g.,"How to effectively mix the CI and CD properties of time series to achieve better predictive performance?"
no code implementations • 22 Aug 2022 • Yuqing Wang, Xiangxian Li, Zhuang Qi, Jingyu Li, Xuelong Li, Xiangxu Meng, Lei Meng
Causal inference has become a powerful tool to handle the out-of-distribution (OOD) generalization problem, which aims to extract the invariant features.