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A prediction rigidity formalism for low-cost uncertainties in trained neural ...
Quantifying the uncertainty of regression models is essential to ensure their reliability, particularly since their application often extends beyond their training domain. Based... -
MASSIVE: Model Assessment and Stochastic Search for Instrumental Variable Est...
The recent availability of huge, many-dimensional data sets, like those arising from genome-wide association studies (GWAS), provides many opportunities for strengthening causal...