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Found 2 papers, 1 papers with code
Self-Supervised Learning for Data Scarcity in a Fatigue Damage Prognostic Problem
This paper aims to investigate whether pre-training DL models in a self-supervised way on unlabelled sensors data can be useful for RUL estimation with only Few-Shots Learning, i. e. with scarce labelled data.
Variance based sensitivity analysis for Monte Carlo and importance sampling reliability assessment with Gaussian processes
Gaussian process based active learning methods for reliability analysis have emerged as a promising way for reducing this computational cost.
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