1k citations · 1.3k across the 26 of their papers we have counts for
26 papers
Source-Free Domain Adaptation via Distribution Estimation
Ning Ding, Yixing Xu, Yehui Tang +3
Domain Adaptation aims to transfer the knowledge learned from a labeled source domain to an unlabeled target domain whose data distributions are different. However, the training da…
An Image Patch is a Wave: Phase-Aware Vision MLP
Yehui Tang, Kai Han, Jianyuan Guo +4
In the field of computer vision, recent works show that a pure MLP architecture mainly stacked by fully-connected layers can achieve competing performance with CNN and transformer.…
Hire-MLP: Vision MLP via Hierarchical Rearrangement
Jianyuan Guo, Yehui Tang, Kai Han +5
Previous vision MLPs such as MLP-Mixer and ResMLP accept linearly flattened image patches as input, making them inflexible for different input sizes and hard to capture spatial inf…
Universal Adder Neural Networks
Hanting Chen, Yunhe Wang, Chang Xu +3
Compared with cheap addition operation, multiplication operation is of much higher computation complexity. The widely-used convolutions in deep neural networks are exactly cross-co…
Federated Learning with Positive and Unlabeled Data
Xinyang Lin, Hanting Chen, Yixing Xu +4
We study the problem of learning from positive and unlabeled (PU) data in the federated setting, where each client only labels a little part of their dataset due to the limitation…
Analogous to Evolutionary Algorithm: Designing a Unified Sequence Model
Jiangning Zhang, Chao Xu, Jian Li +7
Inspired by biological evolution, we explain the rationality of Vision Transformer by analogy with the proven practical Evolutionary Algorithm (EA) and derive that both of them hav…