近日，发表在 Nature Review Physics杂志上的一篇综述论文「Physics-informed machine learning」提出了「教机器学习物理知识以解决物理问题」的观点。该论文回顾了将物理知识嵌入机器学习的流行趋势，介绍了当前的能力和局限性，并讨论了这类机器学习在发现和解决物理中各种正向、逆向问题中的应用。这篇论文虽然只阐述了如...
8. Improvement of scoring functions can be achieved by developing new terms, training on larger high-quality datasets or using sophisticated machine learning-based
This collection will gather the latest advances in physics-informed machine learning applications in sciences and engineering for real world applications.
物理信息机器学习(Physics-informed machine learning,PIML),指的是将物理学的先验知识(历史上自然现象和人类行为的高度抽象),与数据驱动的机器学习模型相结合,这已经成为缓解训练数据短缺、提高模型泛化能力和确保结果的物理合理性的有效途径。在本文中,我们...
"Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations." Journal of Computational physics 378 (2019): 686-707. ^Lu, Lu, et al. "DeepXDE: A deep learning library for solving differential equations." ...
DeepXDE is a library for scientific machine learning and physics-informed learning. DeepXDE includes the following algorithms: physics-informed neural network (PINN) solving different problems solving forward/inverse ordinary/partial differential equations (ODEs/PDEs) [SIAM Rev.] ...
github 上面整理的一个 repo：https://github.com/csjiezhao/Physics-Based-Deep-Learning
“I wanted to take 2.C161 because machine-learning models are usually a “black box,” but this class taught us how to construct a system model that is informed by physics so we can peek inside,” explains Crystal Owens, a mechanical engineering graduate student who took the course in spri...
诺奖| Nobel Prize in Physics 2024 Awarded 2024年诺贝尔物理学奖揭晓 Nobel Prize in physics awarded to 2 scientists for discoveries in machine learning From: AP NEWS John Hopfield and Geoffrey Hinton were awarded the Nobel...
A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems no code yet • 16 Feb 2025 We demonstrate that the resultant value function satisfies a Hamilton-Jacobi-Bellman (HJB) equation, which we approximate efficiently using a novel physics-informed machine ...