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Spatio-temporal DeepKriging for interpolation and probabilistic forecasting, Spatial Statistics

Published in Spatial Statistics, 2023

This paper devises a novel nonparametric approach for prediction of complex spatio-temporal phenomena.

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Bivariate DeepKriging for Computationally Efficient Spatial Interpolation of Large-scale Wind Fields

Published in Technometrics, 2025

In this paper DeepKriging has been extended to bivariate spatial processes, incorporating connections to the Linear Model of Coregionalization.

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Efficient Large-scale Nonstationary Spatial Covariance function estimation using Convolutional Neural Networks

Published in Journal of Computational and Graphical Statistics (JCGS), 2025

This paper provides a data driven scalable approach for fitting Nonstationary Matern covariance for large datasets.

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Efficient Large-scale Nonstationary Spatial Covariance function estimation using Convolutional Neural Networks

Published: August 06, 2022

Presentation on Spatio-temporal DeepKriging for interpolation and probabilistic forecasting

Published: August 07, 2023

Presentation slides are available here

Deep Neural Networks for Large-scale Complex Spatial and Spatio-temporal Processes

Published: May 29, 2024

Presentation slides are available here

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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