AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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These findings establish ICP as a robust and adaptable paradigm for trustworthy class-label uncertainty estimation, particularly within safety-critical workflows such as automated parasite diagnostics.
The results show that the use of suitable encoder-regressor pairs together with embedding-level mix-up augmentation improves model generalizability without requiring SMILES-level augmentation, and could be applied more broadly to IC50 prediction for other kinase inhibitors.
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