TinyBayes delivers 78.7% accuracy on cocoa disease detection with a 9.5 MB edge pipeline that uses YOLOv8-Nano, MobileNetV3-Small, and a closed-form Jacobi-DMR Bayesian classifier.
Blei, Alp Kucukelbir, and Jon D
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
SANODEP meta-learning improves sample efficiency of Bayesian optimization for fed-batch processes over Gaussian processes in low-data regimes on a penicillin production case study.
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TinyBayes: Closed-Form Bayesian Inference via Jacobi Prior for Real-Time Image Classification on Edge Devices
TinyBayes delivers 78.7% accuracy on cocoa disease detection with a 9.5 MB edge pipeline that uses YOLOv8-Nano, MobileNetV3-Small, and a closed-form Jacobi-DMR Bayesian classifier.
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Meta-learning for sample-efficient Bayesian optimisation of fed-batch processes
SANODEP meta-learning improves sample efficiency of Bayesian optimization for fed-batch processes over Gaussian processes in low-data regimes on a penicillin production case study.