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Statistical Deep Learning for Spatial and Spatio-Temporal Data

Statistical Deep Learning for Spatial and Spatio-Temporal Data

C. Wikle
A. Zammit‐Mangion
    BDL
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Papers citing "Statistical Deep Learning for Spatial and Spatio-Temporal Data"

7 / 7 papers shown
Title
Neural Spatiotemporal Point Processes: Trends and Challenges
Neural Spatiotemporal Point Processes: Trends and Challenges
Sumantrak Mukherjee
Mouad Elhamdi
George Mohler
David Selby
Yao Xie
Sebastian Vollmer
Gerrit Grossmann
AI4TS
217
1
0
13 Feb 2025
Neural networks for geospatial data
Neural networks for geospatial data
Wentao Zhan
A. Datta
21
11
0
18 Apr 2023
A New Class of Realistic Spatio-Temporal Processes with Advection and Their Simulation
A New Class of Realistic Spatio-Temporal Processes with Advection and Their Simulation
Maria Laura Battagliola
S. Olhede
34
0
0
05 Mar 2023
ST-PCNN: Spatio-Temporal Physics-Coupled Neural Networks for Dynamics Forecasting
ST-PCNN: Spatio-Temporal Physics-Coupled Neural Networks for Dynamics Forecasting
Yu Huang
James Li
Min Shi
H. Zhuang
Xingquan Zhu
Laurent Chérubin
James H. VanZwieten
Yufei Tang
AI4CE
PINN
23
6
0
12 Aug 2021
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
Xingjian Shi
Zhourong Chen
Hao Wang
Dit-Yan Yeung
W. Wong
W. Woo
236
7,906
0
13 Jun 2015
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
285
9,145
0
06 Jun 2015
Manifold Gaussian Processes for Regression
Manifold Gaussian Processes for Regression
Roberto Calandra
Jan Peters
C. Rasmussen
M. Deisenroth
92
271
0
24 Feb 2014