13 citations · 50 across the 19 of their papers we have counts for
3 papers · 1 filter
Generalisation Through Negation and Predicate Invention
David M. Cerna, Andrew Cropper
The ability to generalise from a small number of examples is a fundamental challenge in machine learning. To tackle this challenge, we introduce an inductive logic programming (ILP…
Differentiable Inductive Logic Programming in High-Dimensional Space
Stanisław J. Purgał, David M. Cerna, Cezary Kaliszyk
Synthesizing large logic programs through symbolic Inductive Logic Programming (ILP) typically requires intermediate definitions. However, cluttering the hypothesis space with inte…
Learning Higher-Order Programs without Meta-Interpretive Learning
Stanisław J. Purgał, David M. Cerna, Cezary Kaliszyk
Learning complex programs through inductive logic programming (ILP) remains a formidable challenge. Existing higher-order enabled ILP systems show improved accuracy and learning pe…