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| [Yali Yuan, yali.yuan@cs.uni-goettingen.de] | | [Yali Yuan, yali.yuan@cs.uni-goettingen.de] | ||
| [http://openaccess.thecvf.com/content_CVPR_2019/papers/Liang_Multi-Task_Multi-Sensor_Fusion_for_3D_Object_Detection_CVPR_2019_paper.pdf] | | [http://openaccess.thecvf.com/content_CVPR_2019/papers/Liang_Multi-Task_Multi-Sensor_Fusion_for_3D_Object_Detection_CVPR_2019_paper.pdf] | ||
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| Physics-informed neural networks: Principles, Case studies, and Prospects | |||
| In this project, you will be devoted to solving a specific problem using | |||
physics-informed neural networks with a small set of experiment data, | |||
which is different from big data driven machine learning. The idea of | |||
using neural networks in the research field of Physics is nowadays more | |||
and more significant. The student is expected to be interested in the | |||
interdisciplinary subject of physics and computer science. | |||
| Basic programming knowledge, Basic machine learning knowledge | |||
| [Yunxiao Zhang, yunxiao.zhang@ds.mpg.de] | |||
| [https://www.sciencedirect.com/science/article/pii/S0045782520305879?via%3Dihub] | |||
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