Projects / dysii

dysii

dysii is a C++ library for distributed probabilistic inference and learning in large-scale dynamical systems. It provides methods such as the Kalman, unscented Kalman, and particle filters and smoothers, as well as useful classes such as common probability distributions and stochastic processes.

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  •  17 Dec 2008 18:24

    Release Notes: This release adds kernel density estimators with distributed kd tree partitioning and dual-tree evaluations, an improved stochastic Runge-Kutta and new Euler-Maruyama integrator for stochastic differential equations, the kernel forward-backward and two-filter smoothers (from the author's PhD work), performance enhancements, and an installation guide.

    •  05 Mar 2008 18:10

      Release Notes: This version adds a stochastic Runge-Kutta method for stochastic differential equations, as well as density and kernel density (KD) trees for representing probability densities.

      •  02 Dec 2007 08:57

        Release Notes: An auxiliary particle filter was added and the resampling strategy framework was generalized. Diagonal covariance detection for optimized Gaussian density calculations was fixed. Several serialization bugs and a Wiener process variance bug were fixed.

        •  09 Oct 2007 21:48

          Release Notes: Overhauled parallel implementations. The particle smoother has been improved with further parallelisation. Distributed storage of mixtures has been added, as well as Gaussian mixture distributions and serialization of probability distributions. A Wiener process variance bug has been fixed.

          •  23 Aug 2007 20:54

            No changes have been submitted for this release.

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