21 citations · 84 across the 26 of their papers we have counts for
30 papers
Coalesced Multi-Output Tsetlin Machines with Clause Sharing
Sondre Glimsdal, Ole-Christoffer Granmo
Using finite-state machines to learn patterns, Tsetlin machines (TMs) have obtained competitive accuracy and learning speed across several benchmarks, with frugal memory- and energ…
Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
Bimal Bhattarai, Ole-Christoffer Granmo, Lei Jiao
The proliferation of fake news, i.e., news intentionally spread for misinformation, poses a threat to individuals and society. Despite various fact-checking websites such as Politi…
Word-level Human Interpretable Scoring Mechanism for Novel Text Detection Using Tsetlin Machines
Bimal Bhattarai, Ole-Christoffer Granmo, Lei Jiao
Recent research in novelty detection focuses mainly on document-level classification, employing deep neural networks (DNN). However, the black-box nature of DNNs makes it difficult…
Enhancing Interpretable Clauses Semantically using Pretrained Word Representation
Rohan Kumar Yadav, Lei Jiao, Ole-Christoffer Granmo +1
Tsetlin Machine (TM) is an interpretable pattern recognition algorithm based on propositional logic, which has demonstrated competitive performance in many Natural Language Process…
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…
Low-Power Audio Keyword Spotting using Tsetlin Machines
Jie Lei, Tousif Rahman, Rishad Shafik +5
The emergence of Artificial Intelligence (AI) driven Keyword Spotting (KWS) technologies has revolutionized human to machine interaction. Yet, the challenge of end-to-end energy ef…