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Found 4 papers, 2 papers with code
Neurosymbolic AI for Reasoning on Biomedical Knowledge Graphs
Biomedical datasets are often modeled as knowledge graphs (KGs) because they capture the multi-relational, heterogeneous, and dynamic natures of biomedical systems.
Machine-Learned Premise Selection for Lean
For this purpose, we designed a custom version of the random forest model, trained in an online fashion.
Neurosymbolic AI for Reasoning over Knowledge Graphs: A Survey
As knowledge graphs are becoming a popular way to represent heterogeneous and multi-relational data, methods for reasoning on graph structures have attempted to follow this neurosymbolic paradigm.
Schemes in Lean
We tell the story of how schemes were formalised in three different ways in the Lean theorem prover.
Algebraic Geometry 14A15, 14-04, 68V20 G.m
