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Feature vs. feature scatter plots with Tc

Visualizing a selection of the most important latent features and how the relate to transition temperature.

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Exploring material classes and their latent representations
By looking at our superconducting state classifier model feature importance, we can understand what features we should be looking at. From there, we can start to study how these features change across
in•18d•updated 17d ago
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Orb latent space features dim-reduced and colored with Tc

Plot produced by taking the features generated by Orb (256 dim output) and visualizing different dimensionality reduction methods on them and coloring the point by Tc from the 3DSC database.

Animated scatter plots showing latent feature evolutions during heating

Here we showcase a few key latent features and their relationships to each other, points colored by their Tc. We animate from 0 K to ~130 K.

SHAP violin plot for Tc classifier model

Shows the distribution of feature importance values across different features

Scatter plot comparing numeric features in the 3DSC dataset

We find a similar idea that high-Tc materials form clusters and are generally a sweet spot within the range of a feature's values.