928 citations · 928 across the 3 of their papers we have counts for
3 papers
Computing Sparse Jacobians and Hessians Using Algorithmic Differentiation
Bradley M. Bell, Kasper Kristensen
Stochastic scientific models and machine learning optimization estimators have a large number of variables; hence computing large sparse Jacobians and Hessians is important. Algori…
TMB: Automatic Differentiation and Laplace Approximation
Kasper Kristensen, Anders Nielsen, Casper W. Berg +2
TMB is an open source R package that enables quick implementation of complex nonlinear random effect (latent variable) models in a manner similar to the established AD Model Builde…
The connection between Bayesian estimation of a Gaussian random field and RKHS
Aleksandr Y. Aravkin, Bradley M. Bell, James V. Burke +1
Reconstruction of a function from noisy data is often formulated as a regularized optimization problem over an infinite-dimensional reproducing kernel Hilbert space (RKHS). The sol…