#inductive learning

try —

2 papers match

cs.DB2026

Fully Inductive Cardinality Estimation

Tim Schwabe, Lukas Ketzer, Maribel Acosta

The paper introduces FICE, a graph neural network‑based estimator that can predict the cardinalities of SPARQL Basic Graph Pattern queries on knowledge graphs it has never seen bef…

#cardinality estimation#graph neural networks#knowledge graphs#sparql query optimization

cs.LG2026

CoDiffGRN: Rethinking Gene Regulatory Network Inference via the BEELINE-KGC Benchmark and Co-evolutionary Discrete Diffusion

Jiaze Song, Runhao Zhao, Minghao Xu +2

The paper introduces a new inductive benchmark (BEELINE‑KGC) and a co‑evolutionary discrete diffusion framework (CoDiffGRN) for inferring gene regulatory networks from single‑cell…

#gene regulatory network inference#single-cell transcriptomics#inductive learning#graph completion