AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Machine Learning-Based Prediction of Cycloplegic Refraction Using the Eyerobo Vision Screener: Design—A Cross-Sectional Comparative Device Study
TabPFN achieved the lowest mean absolute error (MAE) on all Eyerobo scenarios and was competitive with Ridge on auto-refractor scenarios; on the headline Eyerobo Pre + IOL scenario, the per-eye paired difference in MAE between TabPFN and the next-best gradient-boosting learner was 0.117 D in favour of TabPFN.