4 citations · 7 across the 4 of their papers we have counts for
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cs.LG2024★ 2 cited
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning
Peter Eckmann, Dongxia Wu, Germano Heinzelmann +2
Current generative models for drug discovery primarily use molecular docking as an oracle to guide the generation of active compounds. However, such models are often not useful in…
q-bio.BM2024★ 4 cited
MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in Practical Generative Modeling
Peter Eckmann, Dongxia Wu, Germano Heinzelmann +2
Current generative models for drug discovery primarily use molecular docking to evaluate the quality of generated compounds. However, such models are often not useful in practice b…