most citedClarifying Trust of Materials Property Predictions using Neural Networks with Distribution-Specific Uncertainty Quantification

2 citations · 2 across the 1 of their papers we have counts for

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1 paper

cs.LG2023★ 2 cited

Clarifying Trust of Materials Property Predictions using Neural Networks with Distribution-Specific Uncertainty Quantification

Cameron Gruich, Varun Madhavan, Yixin Wang +1

It is critical that machine learning (ML) model predictions be trustworthy for high-throughput catalyst discovery approaches. Uncertainty quantification (UQ) methods allow estimati…