3 papers
cs.DB2023
SPARE: A Single-Pass Neural Model for Relational Databases
Benjamin Hilprecht, Kristian Kersting, Carsten Binnig
While there has been extensive work on deep neural networks for images and text, deep learning for relational databases (RDBs) is still a rather unexplored field. One direction tha…
cs.DB2023
Towards Foundation Models for Relational Databases [Vision Paper]
Liane Vogel, Benjamin Hilprecht, Carsten Binnig
Tabular representation learning has recently gained a lot of attention. However, existing approaches only learn a representation from a single table, and thus ignore the potential…
cs.DB2022
DiffML: End-to-end Differentiable ML Pipelines
Benjamin Hilprecht, Christian Hammacher, Eduardo Reis +2
In this paper, we present our vision of differentiable ML pipelines called DiffML to automate the construction of ML pipelines in an end-to-end fashion. The idea is that DiffML all…