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This paper uses Deep Learning to classify if a display panel with
defects in the manufacturing line can be repaired. Both tabular
data and images are fused together to make predictions, with
separate feature extraction undertaken for each of the modalities.
The model's predictions achieve high Average Precision as well as
robust Precision values in the high Recall regions, which makes it
practical...
We test the usefulness of machine learning (ML) for the valuation and pricing of sovereign risk in the Euro area along two important dimensions: i) its predictive accuracy compared with traditional econometric methods, and ii) its assessment of the main economic factors underlying market perceptions of sovereign risk.We find that ML techniques can capture the dynamics inherent in the market valuation...
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