2025
QUTE: Quantifying Uncertainty in TinyML models with Early-exit-assisted ensembles for model-monitoring
ICML 2025poster
Uncertainty quantification (UQ) provides a resource-efficient solution for on-device monitoring of tinyML models deployed remotely without access to true labels. However, existing UQ methods impose significant memory and compute demands, making them impractical for ultra-low-power, KB-sized tinyML d…