Design of Event-Driven Tsetlin Machines Using Safe Petri Nets
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-61433-0_17
Reference20 articles.
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2. Berge, G.T., Granmo, O.C., Tveit, T.O., Goodwin, M., Jiao, L., Matheussen, B.V.: Using the Tsetlin machine to learn human-interpretable rules for high-accuracy text categorization with medical applications. IEEE Access 7, 115134–115146 (2019). https://doi.org/10.1109/ACCESS.2019.2935416
3. Bhattarai., B., Granmo., O., Jiao., L.: Measuring the novelty of natural language text using the conjunctive clauses of a Tsetlin machine text classifier. In: International Conference on Agents and Artificial Intelligence (ICAART), pp. 410–417. INSTICC, SciTePress (2021). https://doi.org/10.5220/0010382204100417
4. Blakely, C.D.: Tsetlin LOB: realtime regime learning and interpretable prediction in financial limit orderbooks using convolutional Tsetlin machines. In: International Symposium on the Tsetlin Machine (ISTM), pp. 13–20 (2022). https://doi.org/10.1109/ISTM54910.2022.00012
5. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence);CD Blakely,2021
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