21 citations · 23 across the 6 of their papers we have counts for
6 papers
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…
Exploring Effects of Hyperdimensional Vectors for Tsetlin Machines
Vojtech Halenka, Ahmed K. Kadhim, Paul F. A. Clarke +5
Tsetlin machines (TMs) have been successful in several application domains, operating with high efficiency on Boolean representations of the input data. However, Booleanizing compl…
Efficient Data Fusion using the Tsetlin Machine
Rupsa Saha, Vladimir I. Zadorozhny, Ole-Christoffer Granmo
We propose a novel way of assessing and fusing noisy dynamic data using a Tsetlin Machine. Our approach consists in monitoring how explanations in form of logical clauses that a TM…
Building Concise Logical Patterns by Constraining Tsetlin Machine Clause Size
K. Darshana Abeyrathna, Ahmed Abdulrahem Othman Abouzeid, Bimal Bhattarai +8
Tsetlin machine (TM) is a logic-based machine learning approach with the crucial advantages of being transparent and hardware-friendly. While TMs match or surpass deep learning acc…
A Relational Tsetlin Machine with Applications to Natural Language Understanding
Rupsa Saha, Ole-Christoffer Granmo, Vladimir I. Zadorozhny +1
TMs are a pattern recognition approach that uses finite state machines for learning and propositional logic to represent patterns. In addition to being natively interpretable, they…
Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time Scaling
K. Darshana Abeyrathna, Bimal Bhattarai, Morten Goodwin +5
Using logical clauses to represent patterns, Tsetlin Machines (TMs) have recently obtained competitive performance in terms of accuracy, memory footprint, energy, and learning spee…