4 papers
A Real-Time Tsetlin Machine-based Non-intrusive Load Monitoring System on MCUs
Tianhang Tan, Han Wu, Tousif Rahman +3
Non-Intrusive Load Monitoring (NILM) systems estimate individual appliance energy consumption from a single aggregate meter, without requiring separate sensors for each device. By…
Eventizing Traditionally Opaque Binary Neural Networks as 1-safe Petri net Models
Mohamed Tarraf, Alex Chan, Alex Yakovlev +1
Binary Neural Networks (BNNs) offer a low-complexity and energy-efficient alternative to traditional full-precision neural networks by constraining their weights and activations to…
An All-digital 8.6-nJ/Frame 65-nm Tsetlin Machine Image Classification Accelerator
Svein Anders Tunheim, Yujin Zheng, Lei Jiao +3
We present an all-digital programmable machine learning accelerator chip for image classification, underpinning on the Tsetlin machine (TM) principles. The TM is an emerging machin…
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.…