During my research, I have written a number of software packages which are publicly available, subject to some licence restrictions. These packages are described below briefly.
MultiNest (Multi-Modal Nested Sampler) is a Bayesian inference tool, written in Fortran and based on the Nested Sampling algorithm developed by John Skilling, which calculates the evidence and explores the parameter space which may contain multiple posterior modes and pronounced (curving) degeneracies in moderately high dimensions.
MultiNest can be downloaded from this site and used as a standalone sampler for generic use for inference problems, subject to some licence restrictions. If you use MultiNest, please acknowledge the following MultiNest papers in your publications: [arXiv:0704.3704 | arXiv:0809.3437 | arXiv:1306.2144].
SkyNet is an efficient and robust neural network training code for machine learning. It is able to train large and deep feed-forward neural networks, including autoencoders, for use in a wide range of supervised and unsupervised learning applications, such as regression, classification, density estimation, clustering and dimensionality reduction.
SkyNet can be downloaded from this site, subject to some licence restrictions. If you use SkyNet, please acknowledge the following SkyNet papers in your publications: [arXiv:1309.0790 | arXiv:1110.2997].
SuperBayeS (Supersymmetry Parameter Extraction Routines for Bayesian Statistics, developed in collaboration with Roberto Ruiz de Austri and Roberto Trotta) is a package for fast and efficient statistical analysis of supersymmetric theories. It uses Bayesian techniques to explore multidimensional supersymmetry (SUSY) parameter spaces and to compare SUSY predictions with observable quantities, including sparticle masses, collider observables, dark matter abundance, direct detection cross sections, indirect detection quantities etc. Scanning can be performed using Markov Chain Monte Carlo (MCMC) algorithm or more efficiently by employing MultiNest. A full 8-dimensional scan of the CMSSM takes about 12 hours on 10 2.4GHz CPUs using MultiNest.
SuperBayeS can be downloaded from this site. If you use this package, please acknowledge following papers in your publications: [arXiv:hep-ph/0602028 | arXiv:astro-ph/0609126 | arXiv:hep-ph/0611173 | arXiv:0704.3704 | arXiv:0809.3437 | arXiv:0705.2012 | arXiv:0809.3792 | arXiv:1306.2144 | arXiv:1101.3296].