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The main goal of this project is to develop new algorithms of machine learning and collect examples of existing methods. This collection pursues scientific and educational purposes.
This project houses software to analyze data acquired from electrophysiology experiments. Currently, we have an Octave/MATLAB program to analyze electroneurogram traces of coupled oscillators, and a Perl library for the analysis of voltage trace data
Yet Another Audio Feature Extractor is a toolbox for audio analysis. Easy to use and efficient at extracting a large number of audio features simultaneously. WAV and MP3 files supported, or embedding in C++, Python or Matlab applications.
C++, Matlab and Python library for Hidden-state Conditional Random Fields. Implements 3 algorithms: LDCRF, HCRF and CRF. For Windows and Linux, 32- and 64-bits. Optimized for multi-threading. Works with sparse or dense input features.
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CDTB is a MATLAB toolbox which performs Community Detection
...Furthermore, CDTB is designed in a parametric manner so that the user can add his own functions and extensions.
The CDTB can be used in at least three ways. The user can employ the functions from the MATLAB commandline; or he can write his own code, incorporating the CDTB functions; or he can use the Graphical User Interface (GUI) which automates the community detection and includes some data visualization options.
Unix-based preparation and analysis toolbox for molecular simulations
Unix-based preparation and analysis toolbox for Nanomaterials and Room Temperature Ionic Liquids in Bulk and Slab using bash scripts, Gromacs tools and Matlab functions.
NaRIBaS provides a framework that decouples user input parameter and terminal based command lines. NaRIBaS does not replace a simulation software and specific analysis tools like Gromacs, but it allows iterative repetition of tasks while changing specific input parameter.
The toolbox is to be understood as a scripting...
Tools for mass spectrometry, especially for protein mass spectrometry and proteomics: Quantification tools, converters for Applied Biosystems (Q Star and Q Trap), calculation of in-silico fragmentation spectra, converter for Mascot result files
This is a MATLAB toolbox for the quality control and scoring of EMAP and SGA genetic interaction data. It includes a graphical user interface and some automatic plot-generating tools.
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MATLAB Audio Database Toolbox enables easy access and filtering of audio databases such as TIMIT and YOHO by their metadata. The database toolbox comes to replace the manual filtering and custom coding usually required for accessing such databases.
Maximally flat (maxflat) digital filter design for Octave and Matlab. "Maximally flat" means that the magnitude frequency response has the maximum number of vanishing derivatives at 0 and pi. Handles arbitrary numbers of poles and zeros.
Bayesian Surprise Matlab toolkit is a basic toolkit for computing Bayesian surprise values given a large set of input samples. It is also useful as way of exploring surprise theory. For more information see also: http://ilab.usc.edu/
Design and develop Recommendation and Adaptive Prediction Engines to address eCommerce opportunities. Build a portfolio of engines by creating and porting algorithms from multiple disciplines to a usable form. Try to solve NetFlix and other challenges.
nBoost is a suite of boosting algorithms designed to solve binary classification problems on data that is not linearly separable by a convex combination of base hypotheses, i.e. noisy data. WARNING: Active development. Underlying algorithm is unstable.