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Hyperparameter Optimization Tool using Surrogate Modeling and Uncertainty Quantification.

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While there is already a plethora of hyperparameter optimization tools publicly available for machine learning applications, none of them take into account an essential aspect of such models which is that neural network models are built using a stochastic solver approach. The HPO-UQ software was developed with the goal of implementing uncertainty quantification on the models’ parameters.

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