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English(EN) MolSight: Molecular Property Prediction with Images

MolSight 使用图像进行分子性质预测,降低成本

研究人员推出了一种新颖的分子性质预测方法 MolSight,该方法利用分子的图像而非传统的图或三维表示。这种基于视觉的方法在 10 个下游任务中进行了评估,表现出具有竞争力的性能和显著的计算效率,在多个基准测试中取得了顶尖结果,并且 FLOPs 数量远少于多模态竞争对手。该研究还提出了一种化学信息课程来管理不同的结构复杂性,从而提高预测准确性。 AI

排序理由 这是一篇研究论文,详细介绍了一种新的分子性质预测方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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MolSight 使用图像进行分子性质预测,降低成本

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这是一篇研究论文,详细介绍了一种新的分子性质预测方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Aaditya Baranwal, Akshaj Gupta, Yogesh S Rawat, Shruti Vyas ·

    MolSight:利用图像进行分子性质预测

    arXiv:2605.10157v2 Announce Type: replace-cross Abstract: Every molecule ever synthesised can be drawn as a 2D skeletal diagram, yet in modern property prediction this universally available representation has received less focus in favour of molecular graphs, 3D conformers, or bi…