Drug Discovery Synergies
Exploring the parallels between drug discovery and materials science reveals that both fields utilize similar methodologies, particularly with graph neural networks. The design-make-test cycle highlights the differences in experimental throughput, with materials science often requiring more extensive resources. Estimating uncertainty is crucial in both realms, as it informs the development and testing of compounds and materials.In this clip
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
The Physics of Data with Alpha Lee - #377
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