Computer Science > Machine Learning
[Submitted on 11 Sep 2021 (v1), last revised 25 Apr 2022 (this version, v3)]
Title:Physics-based Deep Learning
View PDFAbstract: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 learning from data, we'll look at physical loss constraints, more tightly coupled learning algorithms with differentiable simulations, as well as reinforcement learning and uncertainty modeling. We live in exciting times: these methods have a huge potential to fundamentally change what computer simulations can achieve.
Submission history
From: Nils Thuerey [view email][v1] Sat, 11 Sep 2021 09:38:02 UTC (5,774 KB)
[v2] Fri, 3 Dec 2021 12:07:46 UTC (5,315 KB)
[v3] Mon, 25 Apr 2022 12:36:34 UTC (7,161 KB)
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