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新方法学习图能量以实现有限时间生成

研究人员开发了一种名为有限时间范围能量学习的新方法,用于生成分子图等离散结构。该技术调整了 Metropolis-Hastings 采样器的能量函数,以便在固定步数内生成准确的样本,而不是要求达到平衡。通过使用冻结的预训练模型进行初始化和提议,以及学习到的能量进行接受,该方法在图生成任务上的表现优于传统方法。 AI

影响 这项研究可能为药物发现和材料科学领域更高效、更准确地生成复杂的分子结构带来新的可能。

排序理由 该集群包含一篇详细介绍新机器学习方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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

新方法学习图能量以实现有限时间生成

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该集群包含一篇详细介绍新机器学习方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Amartya Banerjee, Xingyu Xu, Caroline Moosm\"uller, Harlin Lee ·

    为有限时间生成学习图能量

    arXiv:2610.19946v1 Announce Type: new Abstract: Energy-based models can represent distributions over discrete structures such as molecular graphs, but an energy that is accurate at equilibrium need not yield accurate samples when the sampler stops after a fixed number of steps. W…