1 citations · 1 across the 2 of their papers we have counts for
4 papers
Graph Data Augmentation with Contrastive Learning on Covariate Distribution Shift
Fanlong Zeng, Wensheng Gan
Covariate distribution shift occurs when certain structural features present in the test set are absent from the training set. It is a common type of out-of-distribution (OOD) prob…
Pure Node Selection for Imbalanced Graph Node Classification
Fanlong Zeng, Wensheng Gan, Jiayang Wu +1
The problem of class imbalance refers to an uneven distribution of quantity among classes in a dataset, where some classes are significantly underrepresented compared to others. Cl…
GraphIFE: Rethinking Graph Imbalance Node Classification via Invariant Learning
Fanlong Zeng, Wensheng Gan, Philip S. Yu
The class imbalance problem refers to the disproportionate distribution of samples across different classes within a dataset, where the minority classes are significantly underrepr…
Large Language Models for Robotics: A Survey
Fanlong Zeng, Wensheng Gan, Zezheng Huai +5
The human ability to learn, generalize, and control complex manipulation tasks through multi-modality feedback suggests a unique capability, which we refer to as dexterity intellig…