1 code implementation • SIGMOD/PODS 2023 • Jianhong Tu, Ju Fan, Nan Tang, Peng Wang, Guoliang Li, Xiaoyong Du, Xiaofeng Jia, Song Gao
The widely used practice is to build task-specific or even dataset-specific solutions, which are hard to generalize and disable the opportunities of knowledge sharing that can be learned from different datasets and multiple tasks.
1 code implementation • 19 Jan 2023 • Pan Deng, Yu Zhao, Junting Liu, Xiaofeng Jia, Mulan Wang
In addition, due to the disturbance of incomplete observations in the data, random contextual conditions lead to spurious correlations between data and features, making the prediction of the model ineffective in special scenarios.
1 code implementation • 19 Jan 2023 • Yu Zhao, Pan Deng, Junting Liu, Xiaofeng Jia, Mulan Wang
Recent works overemphasize spatio-temporal correlations of traffic flow, ignoring the physical concepts that lead to the generation of observations and their causal relationship.
no code implementations • ICCV 2023 • Wenshuo Ma, Yidong Li, Xiaofeng Jia, Wei Xu
Visual Transformers (ViTs) and Convolutional Neural Networks (CNNs) are the two primary backbone structures extensively used in various vision tasks.