数据驱动动力学系统的开创性理论揭示
ArXiv Stats ML•2026年3月24日 04:00•research▸▾
分析
这项研究真是令人兴奋!它为用于平滑和预测动力学系统的数据驱动方法提供了坚实的理论基础。通用逼近定理的开发是向前迈出的重要一步,有望提高这些人工智能技术的准确性和可靠性。
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"Since the quality of data-driven ROMs is sensitive to the quality of the limited training data, we seek to identify training parameters for which using the associated training data results in the best possible parametric ROM."