Christopher K. Wikle

1. A dimension-reduced approach to space-time Kalman filtering
   1999/12/01 by Christopher K. Wikle, C. Wikle · 15 citations
   Computer Science · Earth and Planetary Sciences · Engineering · #Target Tracking and Data Fusion in Sensor Networks #Geophysics and Gravity Measurements #Inertial Sensor and Navigation
2. A Bayesian adaptive ensemble Kalman filter for sequential state and\n parameter estimation
   2016/11/11 by Jonathan Stroud, Stroud, Jonathan R., Matthias Katzfuß +3 · 3 citations
   Computer Science · Earth and Planetary Sciences · #Bayesian Modeling and Causal Inference #Computation (stat.CO) #FOS: Computer and information sciences #Meteorological Phenomena and Simulations #Methodology (stat.ME) #Neural Networks and Applications #Oceanographic and Atmospheric Processes #Target Tracking and Data Fusion in Sensor Networks
3. A Bayesian Approach for Spatio-Temporal Data-Driven Dynamic Equation Discovery
   2022/09/06 by Joshua S. North, North, Joshua S., Christopher K. Wikle +3 · 5 citations
   Computer Science · Engineering · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Methodology (stat.ME) #Reservoir Engineering and Simulation Methods #Time Series Analysis and Forecasting
4. A Review of Data‐Driven Discovery for Dynamic Systems
   2023/09/29 by Joshua S. North, Christopher K. Wikle, Erin M. Schliep · 6 citations
5. Visualizing uncertainty in areal data with bivariate choropleth maps, map pixelation and glyph rotation
   2017/01/01 by Lydia R Lucchesi, Christopher K. Wikle · 1 voice · 1 citation
   Environmental Science · Medicine · #Data-Driven Disease Surveillance #Remote Sensing in Agriculture #Soil Geostatistics and Mapping
6. Deep Echo State Networks with Uncertainty Quantification for\n Spatio-Temporal Forecasting
   2018/06/27 by Patrick L. McDermott, McDermott, Patrick L., Christopher K. Wikle +1 · 1 citation
   Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Neural Networks and Applications #Neural Networks and Reservoir Computing
7. Bayesian Hierarchical Models with Conjugate Full-Conditional Distributions for Dependent Data from the Natural Exponential Family
   2017/01/25 by Jonathan R. Bradley, Scott H. Holan, Bradley, Jonathan R. +3 · 1 citation
   Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Census and Population Estimation #FOS: Computer and information sciences #Methodology (stat.ME) #Statistical Methods and Bayesian Inference
8. Comparison of Deep Neural Networks and Deep Hierarchical Models for\n Spatio-Temporal Data
   2019/02/21 by Christopher K. Wikle, Wikle, Christopher K. · 1 citation
   Computer Science · Environmental Science · #FOS: Computer and information sciences #Hydrological Forecasting Using AI #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Neural Networks and Reservoir Computing #Remote Sensing in Agriculture
9. On the spatial and temporal shift in the archetypal seasonal temperature\n cycle as driven by annual and semi-annual harmonics
   2020/03/15 by Joshua S. North, Erin M. Schliep, North, Joshua S. +3 · 1 citation
   Economics, Econometrics and Finance · Environmental Science · #Applications (stat.AP) #Atmospheric and Environmental Gas Dynamics #Climate Change Policy and Economics #Climate variability and models #FOS: Computer and information sciences
10. Flexible and efficient emulation of spatial extremes processes via variational autoencoders
    2023/07/16 by Likun Zhang, Zhang, Likun, Xiaoyu Ma +5 · 2 citations
    Earth and Planetary Sciences · Environmental Science · #60G70 #62H11 (Secondary) #68T07 (Primary) #Climate variability and models #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Meteorological Phenomena and Simulations #Methodology (stat.ME) #Oceanographic and Atmospheric Processes
11. Using Echo State Networks to Inform Physical Models for Fire Front Propagation
    2023/02/09 by Myungsoo Yoo, Yoo, Myungsoo, Christopher K. Wikle +1 · 1 citation
    Earth and Planetary Sciences · Environmental Science · #FOS: Computer and information sciences #Fire effects on ecosystems #Meteorological Phenomena and Simulations #Methodology (stat.ME) #Plant Water Relations and Carbon Dynamics
12. Data-Driven Modeling of Wildfire Spread with Stochastic Cellular Automata and Latent Spatio-Temporal Dynamics
    2023/06/05 by Nicholas Grieshop, Christopher K. Wikle, Grieshop, Nicholas +1 · 1 citation
    Computer Science · #Applications (stat.AP) #Cellular Automata and Applications #FOS: Computer and information sciences
13. Calibrated Forecasts of Quasi-Periodic Climate Processes with Deep Echo State Networks and Penalized Quantile Regression
    2023/08/08 by Matthew Bonas, Bonas, Matthew, Christopher K. Wikle +3 · 1 citation
    Computer Science · Earth and Planetary Sciences · #Applications (stat.AP) #Atmospheric and Oceanic Physics (physics.ao-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Neural Networks and Applications #Neural Networks and Reservoir Computing #Oceanographic and Atmospheric Processes