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English(EN) Variational Physics-Informed Ansatz for Reconstructing Hidden Interaction Networks from Steady States

新方法从稳态重构隐藏相互作用网络

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种变分物理信息ansatz，用于从稳态观测中重构隐藏的相互作用网络。该方法将未知算子表示为可训练对象，并最小化跨实验的稳态残差。在特定设置下，堆叠的平衡方程为唯一恢复提供了明确的条件，该条件由考虑了实验规范自由度后的兼容性矩阵的秩决定。合成基准测试表明，当控制动力学已知且节点级平衡被完全观测时，该方法仅使用平衡数据来区分结构的有效性。 AI

排序理由 该集群包含一篇详细介绍重构相互作用网络新方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.LG 阅读 →

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新方法从稳态重构隐藏相互作用网络

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该集群包含一篇详细介绍重构相互作用网络新方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Kaiming Luo ·

    用于从稳态重构隐藏相互作用网络的变分物理信息ansatz

    arXiv:2512.13708v2 Announce Type: replace Abstract: Inferring interaction structure from steady-state observations is a central inverse problem when transient trajectories are unavailable. Here we formulate this problem as simultaneous compatibility of a single interaction operat…

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