Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers , Project: https://github.com/tum-pbs/Solver-in-the-LoopNumerical investigation of minimum drag profiles in laminar flow using deep learning surrogates , PDF: https://arxiv.org/pdf/2009.14339...
METHODS. Recently, physics-based deep learning models to predict the healing outcomes of porcine burns have exploited the rich terahertz spectral data to achieve highly accurate classification on Day 1 after injury. Using a Support Vector Machine and Deep Neural Networks an accuracy between 90 to ...
Deep learning-based remaining useful life estimation of bearings using multi-scale feature extraction Reliab Eng Syst Saf, 182 (2019), pp. 208-218, 10.1016/j.ress.2018.11.011 URL https://www.sciencedirect.com/science/article/pii/S0951832018308299 View PDFView articleGoogle Scholar [39] Yang H...
这本书的名字Physics-based Deep Learning，基于物理的深度学习，表示“物理建模和数值模拟”与“基于人工神经网络的方法”的组合。目的是利用强大的数值技术上，并在任何可能的地方使用这些技术。因此，本书的一个中心目标是，协调以数据为中心的观点与物理模拟之间的关系。由此产生的新方法具有巨大的潜力，可以改进传统...
电子书《Physics-based Deep Learning》基于物理的深度学习书籍(v0.2版)👋O网页链接本文档包含了与物理模拟背景下深度学习相关的一切内容的实用和全面介绍。尽可能地,所有主题都附有Jupyter notebook形式的实践代码示例,以便快速入门。除了标准的从数据中进行监督学习,我们还将探讨物理损失约束、与可微分模拟更紧密耦合...
This digital book contains a practical and comprehensive introduction of everything related to deep learning in the context of physical simulations. As much as possible, all topics come with hands-on code examples in the form of Jupyter notebooks to quickly get started. Beyond standard supervised ...
Deep learning (DL) has emerged as a tool for improving accelerated MRI reconstruction. A common strategy among DL methods is the physics-based approach, where a regularized iterative algorithm alternating between data consistency and a regularizer is unrolled for a finite number of iterations. This...
该存储库收集物理问题深度学习算法的链接,特别强调流体流动,即Navier-Stokes相关问题。它主要收集到TUM的I15实验室的工作链接,以及其他小组的杂项工作。具体可参考下面链接: https:///thunil/Physics-Based-Deep-Learning 下载对应资料,请在公众号回复:物理 ...
Recently, wide attention has been paid to develop deep learning-based models for structural damage identification. However, in most of the studies, the pure deep learning-based structural damage identification methods lack physical interpretability and scientific consistency for generalization. Therefore, al...
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