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Overtraining a neural network for Tc classification · Files on Ouro

2mo

Overtraining a neural network for Tc classification

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Material embedding Tc classifier experiments

Doesn't seem to be much of an effect. Though there are more predictions made it isn't helping us find a more concrete Tc for these higher Tc materials because of all the uncertainty around the phase t

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Raising the classification threshold for Tc estimation

By increasing the level of certainty, requiring a higher probability for superconductivity, it's possible to get better results. However, this kind of tuning usually comes at a cost and other materials will suffer poorer results.

High-Tc superconductor uncertain state classification

Simulating the material heating up to 300 K, we watch as the probability of the superconducting state gradually and steadily decreases, which makes it hard to choose an exact Tc.

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Looking at the model predictions for the 200 K above Tc to get to room temperature, we see consistent and stable predictions for the non-superconducting state.

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Ag0.1In0.9Te1-MP-mp-2597-synth_doped was tested on our classification model, which failed to find Tc and drop probability after Tc.