AD Model Builder, or ADMB, is a powerful software package for the development of state-of-the-art nonlinear statistical models. ADMB is built around the AUTODIF Library, a C language extension which implements reverse mode automatic differentiation. A closely related software package, ADMB-RE, implements random effects in nonlinear models. ADMB was created by David Fournier. And now continues to be developed by the ADMB Project, a creation of the non-profit ADMB Foundation.

The dolfin-adjoint project automatically derives the discrete adjoint and tangent linear models. From a forward model written in the Python interface to DOLFIN. The dolfin-adjoint project aims to solve this problem. We now offer Docker images to simplify the instal.

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This page serves as a communication centre. For a community of researchers working on. Methods that assign probability distributions. To the unknown result of deterministic computations. Tübingen and Michael A Osborne,. Taking this observation seriously, a probabilistic numerical method is a numerical algorithm that takes in a probability distribution over its inputs, and returns a probability distribution over its output.

A library for nonlinear optimization written in Fortran. A library for nonlinear optimization written in Fortran. A low-level Python interface to Cbc, Clp, and Cgl. A Templatized C Framework with Python Bindings for Heuristic Search. Algebraic modeling library in C. Algorithms for K shortest paths.

Seminars, workshops and conferences. Seminars, workshops and conferences. S home page, a group that focuses on theoretical and applied statistics. With an emphasis on applications related to geophysical problems. February 12th 2015 - 14. News related to SAMA topics.