English(EN) DriftingMol: Decoder-Coupled Drift for One-Pass Property-Conditional Molecular Generation

DriftingMol框架增强了属性条件分子生成

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-26 04:00

研究人员开发了DriftingMol，一种用于生成具有特定属性分子的新颖的两阶段框架。该方法将漂移模型适配到SELFIES潜在分子空间，利用解码器的隐藏表示作为漂移特征图。该方法在ZINC250K等数据集上，以低采样成本实现了改进的属性条件生成，并在QED等属性上显示出强相关性。 AI

影响引入了一种低成本的偏属性分子生成机制，有望加速药物发现和材料科学研究。

排序理由该集群包含一篇详细介绍分子生成新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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arXiv cs.LG TIER_1 English(EN) · Jiangjie Qiu, Yijun Li, Wentao Li, Xiaonan Wang · 2026-05-26 04:00

DriftingMol：用于单通道属性条件分子生成的解码器耦合漂移

arXiv:2605.24841v1 Announce Type: new Abstract: Property-conditional molecular generation should produce valid, diverse molecules while responding to continuous target values at low sampling cost. We introduce DriftingMol, a two-stage framework that adapts drifting models to a SE…