Erudite is an application for training and testing back propogation neural networks using the ANNeML (Artifical Neural Network Markup Language) XML format. It supports testing and training neural nets with CSV files and has support for randomized training sets, optional adapting learning rate, sigmoid or hyperbolic tangent transfer functions, optional bias and weight adjustment locking, and more.
Salad (short for Letter Salad) is an efficient and flexible implementation of the well-known anomaly detection method Anagram by Wang et al. (RAID 2006). Salad is based on n-gram models, that is, data is represented as all of its substrings of length n. During training these n-grams are stored in a Bloom filter. This enables the detector to represent a large number of n-grams in little memory and still being able to efficiently access the data. Salad extends Anagram by allowing various n-gram types, a 2-class version of the detector for classification, and various model analysis modes.
Libpointmatcher is a modular "Iterative Closest Point" library, useful for robotics and computer vision. This library is designed with modularity and performance in mind. It provides building blocks to construct various ICP chains often seen in research. These chains can be tuned without any recompilation, and new modules can be added without modifying the core of the library.
G-Code Ripper reads g-code, scales, and rotates and/or splits the tool paths before outputting the modified tool path data to a new g-code file. It evaluates g-code expressions and parameters and interprets YZ and ZX arcs. YZ and ZX arcs are internally converted to linear motions for compatibility with splitting and rotation.
LibBi is used for state-space modelling and Bayesian inference on high-performance computer hardware, including multi-core CPUs, many-core GPUs (graphics processing units), and distributed-memory clusters. The staple methods of LibBi are based on sequential Monte Carlo (SMC), also known as particle filtering. These methods include particle Markov chain Monte Carlo (PMCMC) and SMC2. Other methods include the extended Kalman filter and some parameter optimization routines. LibBi consists of a C++ template library and a parser and compiler, written in Perl, for its own modelling language.
PyParticles is a particle simulation toolbox entirely written in Python. It simulates a particle-by-particle model with the most popular integrations methods, including Euler, Runge Kutta, and Midpoint. It represents the results on an OpenGL or Matplotlib plot, and offers an easy-to-use API.
iNA is a computational tool for quantitative analysis of fluctuations in biochemical reaction networks. Such fluctuations, also known as intrinsic noise, arise due to the stochastic nature of chemical reactions and cannot be ignored for when some molecules are present only in very low copy numbers as is the case in living cells. The SBML-based software computes statistical measures such as means and standard deviations of concentrations within a given accuracy using the analytical system size expansion. The result of iNA’s analysis can be tested against the computationally much more expensive stochastic simulation algorithm.