Orb latent space Tc classifier train and eval dataset Tc histogram

Orb latent space Tc classifier train and eval dataset Tc histogram · Files on Ouro

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Orb latent space Tc classifier train and eval dataset Tc histogram

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Orb latent space Tc classifier evaluation

Careful evaluation of the classifier model is important so that we can truly understand the capabilities and performance of a Tc predicting model. Particularly important to us is the ability for the m

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Orb latent space Tc classifier eval parity plot

Interactive plot of predicted vs. true Tc on the evaluation set.

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3D latent space exploration with Tc

Using the 256 dimensional latent space output from the Orb model, we visualize the 3DSC(MP) dataset using UMAP with direction from Tc labels. Hover a point to see Tc, formula, and Material Project identifier.

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Interactive 3D latent space exploration with Tc

Using the 256 dimensional latent space output from the Orb model, we visualize the 3DSC(MP) dataset using t-SNE and UMAP. The UMAP projection has been given the target for learning a manifold that keeps similar Tc materials close together.

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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.

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