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Thermal Earth Model for the Conterminous United States Using an
  Interpolative Physics-Informed Graph Neural Network (InterPIGNN)

Thermal Earth Model for the Conterminous United States Using an Interpolative Physics-Informed Graph Neural Network (InterPIGNN)

15 March 2024
M. Aljubran
Roland N. Horne
    AI4CE
ArXivPDFHTML

Papers citing "Thermal Earth Model for the Conterminous United States Using an Interpolative Physics-Informed Graph Neural Network (InterPIGNN)"

3 / 3 papers shown
Title
DensePoint: Learning Densely Contextual Representation for Efficient
  Point Cloud Processing
DensePoint: Learning Densely Contextual Representation for Efficient Point Cloud Processing
Yongcheng Liu
Bin Fan
Gaofeng Meng
Jiwen Lu
Shiming Xiang
Chunhong Pan
3DPC
115
269
0
09 Sep 2019
PointNet: Deep Learning on Point Sets for 3D Classification and
  Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
C. Qi
Hao Su
Kaichun Mo
Leonidas J. Guibas
3DH
3DPC
3DV
PINN
219
14,047
0
02 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,109
0
06 Jun 2015
1