DrugFlow, a flow-matching plus Markov-bridge generative model, reports state-of-the-art distributional fidelity for structure-based drug design and adds uncertainty, size adaptation, side-chain flexibility, and preference alignment.
We compare distributions of the first two principal components in Figure
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Multi-domain Distribution Learning for De Novo Drug Design
DrugFlow, a flow-matching plus Markov-bridge generative model, reports state-of-the-art distributional fidelity for structure-based drug design and adds uncertainty, size adaptation, side-chain flexibility, and preference alignment.