AI RESEARCH
Incorporating Deep Learning Design in Database Queries
arXiv CS.LG
•
ArXi:2605.24207v1 Announce Type: cross Deep learning over relational databases is conventionally realized by translating data into graph representations and applying graph-based neural networks within external frameworks. This round-trip between the database and external machine learning (ML) systems We describe RelaNN, a proof-of-concept implementation of this approach built on top of PyTorch and cuDF.