Enhanced Methods for Evolution in-Materio Processors (2022)
Conference Proceeding
Jones, B. A., Al Moubayed, N., Zeze, D. A., & Groves, C. (2022). Enhanced Methods for Evolution in-Materio Processors. . https://doi.org/10.1109/icrc53822.2021.00026

Evolution-in-Materio (EiM) is an unconventional computing paradigm, which uses an Evolutionary Algorithm (EA) to configure a material's parameters so that it can perform a computational task. While EiM processors show promise, slow manufacturing and... Read More about Enhanced Methods for Evolution in-Materio Processors.

Confidence Measures for Carbon-Nanotube / Liquid Crystals Classifiers (2018)
Conference Proceeding
Vissol-Gaudin, E., Kotsialos, A., Groves, C., Pearson, C., Zeze, D., Petty, M., & Al-moubayed, N. (2018). Confidence Measures for Carbon-Nanotube / Liquid Crystals Classifiers. In 2018 IEEE Congress on Evolutionary Computation (CEC) : 8-13 July 2018, Rio de Janeiro, Brazil ; proceedings (646-653). https://doi.org/10.1109/cec.2018.8477779

This paper focuses on a performance analysis of single-walled-carbon-nanotube / liquid crystal classifiers produced by evolution in materio. A new confidence measure is proposed in this paper. It is different from statistical tools commonly used to e... Read More about Confidence Measures for Carbon-Nanotube / Liquid Crystals Classifiers.