Christopher K. Wikle

According to our database, Christopher K. Wikle authored at least 19 papers between 2003 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2026

Capturing extreme events in turbulence using an extreme variational autoencoder (xVAE).

Likun Zhang, Kiran Bhaganagar, Christopher K. Wikle

Neural Comput. Appl., June, 2026

2025

Modeling Spatio-temporal Extremes via Conditional Variational Autoencoders.

Xiaoyu Ma, Likun Zhang, Christopher K. Wikle

CoRR, December, 2025

2024

Echo State Networks for Spatio-Temporal Area-Level Data.

Zhenhua Wang, Scott H. Holan, Christopher K. Wikle

CoRR, 2024

Uncertainty-enabled machine learning for emulation of regional sea-level change caused by the Antarctic Ice Sheet.

Myungsoo Yoo, Giri Gopalan, Matthew J. Hoffman, Sophie Coulson, Holly Kyeore Han, Christopher K. Wikle, Trevor Hillebrand

CoRR, 2024

2023

Correcting for informative sampling in spatial covariance estimation and kriging predictions.

Erin M. Schliep, Christopher K. Wikle, Ranadeep Daw

J. Geogr. Syst., October, 2023

Flexible and efficient spatial extremes emulation via variational autoencoders.

Likun Zhang, Xiaoyu Ma, Christopher K. Wikle, Raphaël Huser

CoRR, 2023

2022

Statistical Deep Learning for Spatial and Spatio-Temporal Data.

Christopher K. Wikle, Andrew Zammit-Mangion

CoRR, 2022

2021

Vizumap: an R package for visualising uncertainty in spatial data.

Lydia R. Lucchesi, Petra M. Kuhnert, Christopher K. Wikle

J. Open Source Softw., 2021

Spatio-temporal change of support modeling with R.

Andrew M. Raim, Scott H. Holan, Jonathan R. Bradley, Christopher K. Wikle

Comput. Stat., 2021

2020

Bayesian Inverse Reinforcement Learning for Collective Animal Movement.

Toryn L. J. Schafer, Christopher K. Wikle, Mevin B. Hooten

CoRR, 2020

2019

Bayesian Recurrent Neural Network Models for Forecasting and Quantifying Uncertainty in Spatial-Temporal Data.

Patrick L. McDermott, Christopher K. Wikle

Entropy, 2019

Deep Integro-Difference Equation Models for Spatio-Temporal Forecasting.

Andrew Zammit-Mangion, Christopher K. Wikle

CoRR, 2019

Comparison of Deep Neural Networks and Deep Hierarchical Models for Spatio-Temporal Data.

Christopher K. Wikle

CoRR, 2019

2018

Hierarchical (Deep) Echo State Networks with Uncertainty Quantification for Spatio-Temporal Forecasting.

Patrick L. McDermott, Christopher K. Wikle

CoRR, 2018

2017

Hierarchical Spatial Models.

Ali Arab, Mevin B. Hooten, Christopher K. Wikle

Proceedings of the Encyclopedia of GIS., 2017

2008

Hierarchical Spatial Models.

Ali Arab, Mevin B. Hooten, Christopher K. Wikle

Proceedings of the Encyclopedia of GIS., 2008

2005

Combining Information Across Spatial Scales.

Christopher K. Wikle, L. Mark Berliner

Technometrics, 2005

Atmospheric Modeling, Data Assimilation, and Predictability.

Christopher K. Wikle

Technometrics, 2005

2003

Modeling Hydrologic Change: Statistical Methods.

Christopher K. Wikle

Technometrics, 2003