When and why PINNs fail to train: A neural tangent kernel pe...

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This research explores When and why PINNs fail to train: A neural tangent kernel pe..., contributing new insights to the field of Artificial Intelligence.

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Research demonstrates significant advances in performance benchmarks
Study provides new evidence regarding model accuracy improvements
Findings open new directions for computational efficiency

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This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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📋 Article Details

Category	🤖 Artificial Intelligence
Published	Oct 12, 2021
Journal	Journal of Computational Physics
Authors	Sifan Wang, Xinling Yu, Paris Perdikaris
DOI	10.1016/j.jcp.2021.110768
Citations	1,146
Source	OpenAlex

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🤖 Artificial Intelligence 🧬 Medicine & Biology ⚛️ Physics & Space Science ⚙️ Engineering & Technology ∑ Mathematics

When and why PINNs fail to train: A neural tangent kernel perspective

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