Better with less: A data-active perspective on pre-training graph neural networks

J Xu, R Huang, X Jiang, Y Cao… - Advances in …, 2023 - proceedings.neurips.cc
Pre-training on graph neural networks (GNNs) aims to learn transferable knowledge for
downstream tasks with unlabeled data, and it has recently become an active research area …

Self-supervised pre-training for transformer-based person re-identification

H Luo, P Wang, Y Xu, F Ding, Y Zhou, F Wang… - ar** foundational neural Partial
Differential Equation (PDE) solvers and neural operators through large-scale pretraining …

Feature augmentation and semi-supervised conditional transfer learning for early detection of sepsis

Y Dou, W Li, Y Nan, Y Zhang, S Peng - Computers in Biology and Medicine, 2023 - Elsevier
Early detection of Sepsis is crucial for improving patient outcomes, as it is a significant public
health concern that results in substantial morbidity and mortality. However, despite the …