Automatic approximation of the marginal likelihood in non-Gaussian hierarchical models. - Hans J. Skaug; David A. Fournier (Comput. Stat. Data Anal., 2006)

Fitting general stochastic volatility models using Laplace accelerated sequential importance sampling. - Tore Selland Kleppe; Hans Julius Skaug (Comput. Stat. Data Anal., 2012)

AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models. - David A. Fournier; Hans J. Skaug; Johnoel Ancheta; James Ianelli; Arni Magnusson; Mark N. Maunder; Anders Nielsen 002; John Sibert (Optim. Methods Softw., 2012)

A flexible and automated likelihood based framework for inference in stochastic volatility models. - Hans J. Skaug; Jun Yu 006 (Comput. Stat. Data Anal., 2014)

Determining Individual Variation in Growth and Its Implication for Life-History and Population Processes Using the Empirical Bayes Method. - Simone Vincenzi; Marc Mangel; Alain J. Crivelli; Stephan Munch; Hans J. Skaug (PLoS Comput. Biol., 2014)

Bandwidth selection in pre-smoothed particle filters. - Tore Selland Kleppe; Hans J. Skaug (Stat. Comput., 2016)

glmmTMB Balances Speed and Flexibility Among Packages for Zero-inflated Generalized Linear Mixed Modeling. - Mollie E. Brooks; Kasper Kristensen; Koen J. van Benthem; Arni Magnusson; Casper W. Berg; Anders Nielsen 002; Hans J. Skaug; Martin Mächler; Benjamin M. Bolker (R J., 2017)

On the application of improved symplectic integrators in Hamiltonian Monte Carlo. - Janne Mannseth; Tore Selland Kleppe; Hans J. Skaug (Commun. Stat. Simul. Comput., 2018)

Efficient Computation of Hessian Matrices in TensorFlow. - Geir Kjetil Nilsen; Antonella Zanna Munthe-Kaas; Hans J. Skaug; Morten Brun (CoRR, 2019)

On the Delta Method for Uncertainty Approximation in Deep Learning. - Geir Kjetil Nilsen; Antonella Zanna Munthe-Kaas; Hans J. Skaug; Morten Brun (CoRR, 2019)

A Comparison of the Delta Method and the Bootstrap in Deep Learning Classification. - Geir Kjetil Nilsen; Antonella Zanna Munthe-Kaas; Hans J. Skaug; Morten Brun (CoRR, 2021)

Epistemic uncertainty quantification in deep learning classification by the Delta method. - Geir Kjetil Nilsen; Antonella Zanna Munthe-Kaas; Hans J. Skaug; Morten Brun (Neural Networks, 2022)

A TMB Approach to Study Spatial Variation in Weather-Generated Claims in Insurance. - Ingrid Sandvig Thorsen; Bård Støve; Hans J. Skaug (Oper. Res. Forum, 2023)

Sparse Bayesian learning using TMB (Template Model Builder). - Ingvild M. Helgøy; Hans J. Skaug; Yushu Li (Stat. Comput., 2024)