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Mar, 2025
去噪哈密顿网络用于物理推理
Denoising Hamiltonian Network for Physical Reasoning
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Congyue Deng, Brandon Y. Feng, Cecilia Garraffo, Alan Garbarz, Robin Walters...
TL;DR
本文解决了传统物理问题机器学习方法在建模时对长程物理交互和更广泛推理任务的忽视。提出的去噪哈密顿网络(DHN)通过灵活的神经算子捕捉非局部的时间关系,并通过去噪机制减小数值积分误差。研究表明,DHN在多系统建模和三种不同物理推理任务中展示了其有效性和灵活性。
Abstract
Machine Learning
frameworks for physical problems must capture and enforce physical constraints that preserve the structure of dynamical systems. Many existing approaches achieve this by integrating physical operators into
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