CliffSplit exposes at least 15% higher errors in cliff-heavy regions of QM9 while CliffLoss narrows the cliff-to-smooth error gap by up to 30% and improves overall MAE by 9.7% across several molecular tasks and backbones.
Schnet: A continuous-filter convolutional neural network for modeling quantum interactions.Advances in Neural Information Processing Systems, 30, 2017
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When Molecular Similarity Works: Property Cliffs Reveal Hidden Errors
CliffSplit exposes at least 15% higher errors in cliff-heavy regions of QM9 while CliffLoss narrows the cliff-to-smooth error gap by up to 30% and improves overall MAE by 9.7% across several molecular tasks and backbones.