【Research Highlights】NYCU researchers develop an efficient shallow neural network to solve surface PDEs and PDEs with singularities

Full metadata record

DC Field	Value	Language
dc.contributor.author	國際事務處	zh_TW
dc.contributor.author	Office of International Affairs	en_US
dc.date.accessioned	2022-08-22T00:06:50Z	-
dc.date.available	2022-08-22T00:06:50Z	-
dc.date.issued	2022-08-01	en_US
dc.identifier.uri	https://en.nycu.edu.tw/an-efficient-shallow-neural-network-to-solve-surface-pdes-and-pdes-with-singularities/	en_US
dc.identifier.uri	https://drive.google.com/file/d/115gV65drEonnrCgUZKAX3W2FAjNBMtuN/view	en_US
dc.identifier.uri	http://hdl.handle.net/11536/157366	-
dc.description.abstract	Researchers in the Mathematical and Scientific Machine Learning Laboratory (MSML) leading by Prof. Ming-Chih Lai at Department of Applied Mathematics in NYCU investigate computational fluid mechanics and explore potential machine learning approaches in solving fluid- structure interaction problems.	en_US
dc.language.iso	en_US	en_US
dc.publisher	國立陽明交通大學	zh_TW
dc.publisher	National Yang Ming Chiao Tung University	en_US
dc.title	【Research Highlights】NYCU researchers develop an efficient shallow neural network to solve surface PDEs and PDEs with singularities	en_US
dc.type	Historical News	en_US
dc.identifier.journal	陽明交大英文電子報	zh_TW
dc.identifier.journal	NYCU E-NEWS	en_US
dc.citation.issue	2022-08	en_US
Appears in Collections:	NYCU E-NEWS

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