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Found 3 papers, 1 papers with code
Multivariate Density Estimation with Missing Data
Multivariate density estimation is a popular technique in statistics with wide applications including regression models allowing for heteroskedasticity in conditional variances.
Methodology
Learning Gaussian Graphical Models Using Discriminated Hub Graphical Lasso
When no hubs are known, we use Graphical Lasso (GL) to provide information of hubs and find that the performance of DHGL will always be better than HGL if correct prior information is given and will seldom degenerate when the prior information is wrong.
Rethinking ResNets: Improved Stacking Strategies With High Order Schemes
We show that the widely used DNN design strategy, constantly stacking a small design (usually 2-3 layers), could be easily improved, supported by solid theoretical knowledge and with no extra parameters needed.
