3 papers
cs.LG2026
The Tsetlin Machine Goes Deep: Logical Learning and Reasoning With Graphs
Ole-Christoffer Granmo, Youmna Abdelwahab, Per-Arne Andersen +12
Pattern recognition with concise and flat AND-rules makes the Tsetlin Machine (TM) both interpretable and efficient, while the power of Tsetlin automata enables accuracy comparable…
cs.LG2025
Scalable Bayesian Network Structure Learning Using Tsetlin Machine to Constrain the Search Space
Kunal Dumbre, Lei Jiao, Ole-Christoffer Granmo
The PC algorithm is a widely used method in causal inference for learning the structure of Bayesian networks. Despite its popularity, the PC algorithm suffers from significant time…
cs.LG2025
Uncertainty Quantification in the Tsetlin Machine
Runar Helin, Ole-Christoffer Granmo, Mayur Kishor Shende +5
Data modeling using Tsetlin machines (TMs) is all about building logical rules from the data features. The decisions of the model are based on a combination of these logical rules.…