Latest Research
HiQR: An efficient algorithm for high dimensional quadratic regression with penalties
This paper investigates the efficient solution of penalized quadratic regressions in high-dimensional settings.
Computation
Bayesian Image Analysis in Fourier Space
The Bayesian image analysis in Fourier space (BIFS) approach proposed here reformulates the conventional Bayesian image analysis paradigm as a large set of independent (but heterogeneous) processes over Fourier space.
Methodology
Sensitivity analysis for publication bias on the time-dependent summary ROC analysis in meta-analysis of prognosis studies
In the analysis of prognosis studies with time-to-event outcomes, dichotomization of patients is often made.
Methodology Applications
Estimating excess mortality in high-income countries during the COVID-19 pandemic
Quantifying the number of deaths caused by the COVID-19 crisis has been an ongoing challenge for scientists, and no golden standard to do so has yet been established.
Applications Methodology
Non-stationary Gaussian Process Surrogates
We provide a survey of non-stationary surrogate models which utilize Gaussian processes (GPs) or variations thereof, including non-stationary kernel adaptations, partition and local GPs, and spatial warpings through deep Gaussian processes.
Methodology
Model averaging approaches to data subset selection
jwsitison/data_subset_variation
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Often, it is useful to consider data subset selection at the same time, in which model selection criteria are used to compare models across different subsets of the data.
Methodology High Energy Physics - Lattice
Heterogeneous Matrix Factorization: When Features Differ by Datasets
We show that under appropriate conditions on the alignment of source-specific factors, the problem is well-defined and both shared and source-specific factors are identifiable under a constrained matrix factorization objective.
Methodology
CRAN Task Views: The Next Generation
CRAN Task Views have been available on the Comprehensive R Archive Network since 2005.
Computation
Mortality Forecasting using Variational Inference
This paper considers the problem of forecasting mortality rates.
Applications
The GNAR-edge model: A network autoregressive model for networks with time-varying edge weights
In economic and financial applications, there is often the need for analysing multivariate time series, comprising of time series for a range of quantities.
Methodology Applications
