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The detection of out-of-distribution (OoD) samples is crucial for deploying deep learning (DL) models in real-world scenarios. OoD samples pose a challenge to DL models as they are not represented
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structural characteristics is therefore crucial. Atomistic investigations have already been conducted on liquid uranium-zirconium mixtures, successfully establishing predictive models for these relationships
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experimentation with innovative modeling, data analysis and machine learning/AI techniques. 1 - Global Energy-Economy-Environment Systems Modelling Your main duty is to contribute to our collection of linear
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JOIN US, TO DO WHAT? Contributing to technological innovation for clean and safe energy, health and well-being, sustainable transportation, information and communications, space exploration, safety and
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focuses on the analytical synthesis of broadband and dual-band matching networks and power combiners for 6G radar applications. The objective is to develop a component library for integration