Compressed Continuous Computation (C3) (Github)
The Compressed Continuous Computation (C3) library (in C) enables computation with multivariate functions. Many multilinear algebra computations are included. Common tasks include addition, multiplication, integration, differentiation, and approximation of multivariate functions.
Doxygen based documentation is available here.
Stochastic Optimal Control with compressed continuous computation (C3SC) (Github)
The C3SC add-on to the C3 package provides utilities for solving general stochastic optimal control problems. The included algorithms can handle non-affine controls and non-quadratic costs. The underlying theory is based on low-rank representations of value functions.
Experimental design for Gaussian process regression (GPEXP) (Github)
GPEXP is a software package, written in python2.7, for performing experimental design in the context of Gaussian process (GP) regression. Experimental design may be performed for a variety of cost function specifications. Currently supported cost functions include those based on integrated variance, conditional entropy, and mutual information. GPEXP may also be used for general purpose GP regression. Currently supported kernels include the isotropic and anisotropic squared exponential kernel, the isotropic Matern kernel, and the Mehler kernel. Additional kernels may be easily specified. GPEXP also includes optimization routines for estimating kernel hyperparameters from data.