In a continued development of patent eligibility policy following Ex parte Desjardins, the Patent Trial and Appeal Board ...
Machine learning algorithms create potentially more accurate models than linear models, but any increase in accuracy over more traditional, better-understood, and more easily explainable techniques is ...
With major code and visualization clean up contributions done by Matthew Epland (@mepland). To interopt with these different libraries, dtreeviz uses an adaptor object, obtained from function dtreeviz ...
Mellon, J., and Worrell, C., 2023: Explainability in Cybersecurity Data Science. Software Engineering Institute blog, Accessed July 8, 2026, https://doi.org/10.58012 ...
Abstract: Autonomous underwater vehicles (AUVs) typically rely on underwater sound to communicate with sound channel physics defining communication performance. Current acoustic propagation models ...
Abstract: As known to all, problems consume more and more computational resources, for example, memory and time, with the gradual enhancements of both the size of the physical domain and complexity in ...
Machine learning (ML) methods developed to assist in detecting stroke have focused on interpreting detailed clinical data such as clinical notes and diagnostic imaging results. However, such ...
Last year, a strange self-driving car was released onto the quiet roads of Monmouth County, New Jersey. The experimental vehicle, developed by researchers at the chip maker Nvidia, didn’t look ...
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