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Using what we learned when trying to use the MLFF's latent space for Tc prediction, there's a way we can simplify things for the prediction model and give it a better change of picking up on the signa
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Visualizing the counts of materials in the training and evaluation dataset by their Tc. First bin is non-superconductors, the rest are ranges of 20 K increments.
Interactive plot of predicted vs. true Tc on the evaluation set.
Not a very robust report yet. We're not through all the data points and these results come from a few different models (trained with more data as it came available)
From the 3465 configurations, representing X materials, we have the following ROC curve.