Hans J. Skaug

Publication Activity (10 Years)

Years Active: 2006-2023
Publications (10 Years): 8

Top Topics

Generalized Linear

Top Venues

Oper. Res. Forum

Publications

Ingrid Sandvig Thorsen, Bård Støve, Hans J. Skaug
A TMB Approach to Study Spatial Variation in Weather-Generated Claims in Insurance. Oper. Res. Forum 4 (4) (2023)
Geir Kjetil Nilsen, Antonella Zanna Munthe-Kaas, Hans J. Skaug, Morten Brun
Epistemic uncertainty quantification in deep learning classification by the Delta method. Neural Networks 145 (2022)
Geir Kjetil Nilsen, Antonella Zanna Munthe-Kaas, Hans J. Skaug, Morten Brun
A Comparison of the Delta Method and the Bootstrap in Deep Learning Classification. CoRR (2021)
Geir Kjetil Nilsen, Antonella Zanna Munthe-Kaas, Hans J. Skaug, Morten Brun
Efficient Computation of Hessian Matrices in TensorFlow. CoRR (2019)
Geir Kjetil Nilsen, Antonella Zanna Munthe-Kaas, Hans J. Skaug, Morten Brun
On the Delta Method for Uncertainty Approximation in Deep Learning. CoRR (2019)
Janne Mannseth, Tore Selland Kleppe, Hans J. Skaug
On the application of improved symplectic integrators in Hamiltonian Monte Carlo. Commun. Stat. Simul. Comput. 47 (2) (2018)
Mollie E. Brooks, Kasper Kristensen, Koen J. van Benthem, Arni Magnusson, Casper W. Berg, Anders Nielsen, Hans J. Skaug, Martin Mächler, Benjamin M. Bolker
glmmTMB Balances Speed and Flexibility Among Packages for Zero-inflated Generalized Linear Mixed Modeling. R J. 9 (2) (2017)
Tore Selland Kleppe, Hans J. Skaug
Bandwidth selection in pre-smoothed particle filters. Stat. Comput. 26 (5) (2016)
Simone Vincenzi, Marc Mangel, Alain J. Crivelli, Stephan Munch, Hans J. Skaug
Determining Individual Variation in Growth and Its Implication for Life-History and Population Processes Using the Empirical Bayes Method. PLoS Comput. Biol. 10 (9) (2014)
Hans J. Skaug, Jun Yu
A flexible and automated likelihood based framework for inference in stochastic volatility models. Comput. Stat. Data Anal. 76 (2014)
David A. Fournier, Hans J. Skaug, Johnoel Ancheta, James Ianelli, Arni Magnusson, Mark N. Maunder, Anders Nielsen, John Sibert
AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models. Optim. Methods Softw. 27 (2) (2012)
Hans J. Skaug, David A. Fournier
Automatic approximation of the marginal likelihood in non-Gaussian hierarchical models. Comput. Stat. Data Anal. 51 (2) (2006)