arXiv Machine Learning August 14, 2026 By Pongpisit Thanasutives, Yoshinobu Kawahara

Robust data-driven discovery of fractional differential equations via weak formulations and Pareto-based subset selection

Read the original on arXiv Machine Learning →

arXiv:2608. 12879v1 Announce Type: new Abstract: Fractional partial differential equations describe nonlocal dynamics, but discovering them from noisy data is difficult because fractional differentiation amplifies high-frequency measurement noise and the derivative orders are unknown.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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