Article

Model Agnostic Semi-Supervised Meta-Learning Elucidates Understudied Out-of-distribution Molecular Interactions

2023-05-20

Abstract excerpt

Many biological problems are understudied due to experimental limitations and human biases. Although deep learning is promising in accelerating scientific discovery, its power compromises when applied to problems with scarcely labeled data and data distribution shifts. We developed a semi-supervised meta learning framework Meta Model Agnostic Pseudo Label Learning (MMAPLE) to address these challenges by effectivel...

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Literature Corpus work: 7c3cdbf2-70b0-55e1-a06a-59d04b33b757
DOI: 10.1101/2023.05.17.541172

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