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09/16/2022
Covariance regression with random forests
Capturing the conditional covariances or correlations among the elements...
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08/21/2022
Bayesian Complementary Kernelized Learning for Multidimensional Spatiotemporal Data
Probabilistic modeling of multidimensional spatiotemporal data is critic...
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09/24/2021
Spatial Aggregation and Temporal Convolution Networks for Real-time Kriging
Spatiotemporal kriging is an important application in spatiotemporal dat...
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08/31/2021
Scalable Spatiotemporally Varying Coefficient Modeling with Bayesian Kernelized Tensor Regression
As a regression technique in spatial statistics, spatiotemporally varyin...
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06/15/2021
RFpredInterval: An R Package for Prediction Intervals with Random Forests and Boosted Forests
Like many predictive models, random forests provide a point prediction f...
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01/18/2021
Detecting differentially methylated regions in bisulfite sequencing data using quasi-binomial mixed models with smooth covariate effect estimates
Identifying disease-associated changes in DNA methylation can help to ga...
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11/23/2020
Conditional canonical correlation estimation based on covariates with random forests
Investigating the relationships between two sets of variables helps to u...
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06/13/2020
Inductive Graph Neural Networks for Spatiotemporal Kriging
Time series forecasting and spatiotemporal kriging are the two most impo...
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04/23/2020
Inference for travel time on transportation networks
Travel time is essential for making travel decisions in real-world trans...
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11/18/2018