English(EN) FoundPDE: A generative foundation model for data-driven symbolic discovery of partial differential equations

FoundPDE：用于PDE符号发现的新基础模型

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-21 04:00

研究人员开发了FoundPDE，一个用于从数据中符号发现偏微分方程（PDE）的生成式基础模型。这个基于Transformer的模型利用傅里叶和空间导数增强来提取轨迹信息和优化系数。FoundPDE在20个PDE家族的基准测试中表现强劲，实现了97.50%的类型识别率，并在系数偏移和噪声下保持鲁棒性。该模型还支持少样本微调以发现未见的复合方程，并能用有限的额外数据扩展到新的物理领域。 AI

影响能够直接从数据中更高效、更通用地发现科学定律。

排序理由该集群包含一篇详细介绍新的符号发现模型的论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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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Signal score: 0 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 该集群包含一篇详细介绍新的符号发现模型的论文。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: paper, model release; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: 5 days old; Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Langchen Liu, Junlin Luo, Min Zhu, Zhuoran Yang, Lu Lu · 2026-10-21 04:00

FoundPDE：一种用于数据驱动的偏微分方程符号发现的生成式基础模型

arXiv:2610.26963v1 Announce Type: cross Abstract: Discovering governing partial differential equations (PDEs) from observed data is a central inverse problem in computational science and engineering: the goal is not only to predict trajectories, but to identify interpretable symb…

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报道来源 [1]

FoundPDE：一种用于数据驱动的偏微分方程符号发现的生成式基础模型

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