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BibTex format

@article{Cheng:2025:10.1016/j.inffus.2025.103255,
author = {Cheng, S and Bocquet, M and Ding, W and Finn, TS and Fu, R and Fu, J and Guo, Y and Johnson, E and Li, S and Liu, C and Moroi, EN and Panj, J and Piggott, M and Quilodran, C and Sharma, P and Wang, K and Xiao, D and Xue, X and Zeng, Y and Zhang, M and Zhou, H and Zhu, K and Arcucci, R},
doi = {10.1016/j.inffus.2025.103255},
journal = {INFORMATION FUSION},
title = {Machine learning for modelling unstructured grid data in computational physics: A review},
url = {http://dx.doi.org/10.1016/j.inffus.2025.103255},
volume = {123},
year = {2025}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AU  - Cheng,S
AU  - Bocquet,M
AU  - Ding,W
AU  - Finn,TS
AU  - Fu,R
AU  - Fu,J
AU  - Guo,Y
AU  - Johnson,E
AU  - Li,S
AU  - Liu,C
AU  - Moroi,EN
AU  - Panj,J
AU  - Piggott,M
AU  - Quilodran,C
AU  - Sharma,P
AU  - Wang,K
AU  - Xiao,D
AU  - Xue,X
AU  - Zeng,Y
AU  - Zhang,M
AU  - Zhou,H
AU  - Zhu,K
AU  - Arcucci,R
DO  - 10.1016/j.inffus.2025.103255
PY  - 2025///
SN  - 1566-2535
TI  - Machine learning for modelling unstructured grid data in computational physics: A review
T2  - INFORMATION FUSION
UR  - http://dx.doi.org/10.1016/j.inffus.2025.103255
VL  - 123
ER  -
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