2 papers
cs.DB2026
RDBLearn: Simple In-Context Prediction Over Relational Databases
Yanlin Zhang, Linjie Xu, Quan Gan +2
Recent advances in tabular in-context learning (ICL) show that a single pretrained model can adapt to new prediction tasks from a small set of labeled examples, avoiding per-task t…
cs.DC2023
GNNFlow: A Distributed Framework for Continuous Temporal GNN Learning on Dynamic Graphs
Yuchen Zhong, Guangming Sheng, Tianzuo Qin +3
Graph Neural Networks (GNNs) play a crucial role in various fields. However, most existing deep graph learning frameworks assume pre-stored static graphs and do not support trainin…