3 papers
cs.LG2026
Preventing Data Leakage in EEG-Based Survival Prediction: A Two-Stage Embedding and Transformer Framework
Yixin Zhou, Zhixiang Liu, Vladimir I. Zadorozhny +1
Deep learning models have shown promise in EEG-based outcome prediction for comatose patients after cardiac arrest, but their reliability is often compromised by subtle forms of da…
cs.LG2025
A Methodology for Transparent Logic-Based Classification Using a Multi-Task Convolutional Tsetlin Machine
Mayur Kishor Shende, Ole-Christoffer Granmo, Runar Helin +2
The Tsetlin Machine (TM) is a novel machine learning paradigm that employs finite-state automata for learning and utilizes propositional logic to represent patterns. Due to its sim…
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.…