67 citations · 117 across the 9 of their papers we have counts for
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stat.ME2023★ 67 cited
Automatic cross-validation in structured models: Is it time to leave out leave-one-out?
A. Adin, E. Krainski, A. Lenzi +3
Standard techniques such as leave-one-out cross-validation (LOOCV) might not be suitable for evaluating the predictive performance of models incorporating structured random effects…
stat.ME2023★ 11 cited
Neural Likelihood Surfaces for Spatial Processes with Computationally Intensive or Intractable Likelihoods
Julia Walchessen, Amanda Lenzi, Mikael Kuusela
In spatial statistics, fast and accurate parameter estimation, coupled with a reliable means of uncertainty quantification, can be challenging when fitting a spatial process to rea…
stat.ML2023★ 3 cited
Towards black-box parameter estimation
Amanda Lenzi, Haavard Rue
Deep learning algorithms have recently shown to be a successful tool in estimating parameters of statistical models for which simulation is easy, but likelihood computation is chal…