CoRoPa stands for Computational Rough Paths. The aim of CoRoPa is to provide a software framework for various ideas related to Rough Path Theory, including rough differential equations and the digital description of serial data streams.
An implementation of the Kernel-based Orthogonal Projections to Latent Structures (K-OPLS) method for MATLAB and R. The supplied functionality includes e.g. cross-validation, kernel parameter optimization, model diagnostics and plot tools.
BRAHMS is a Modular Execution Framework for dynamical systems. It knits together independently-authored software modules implementing dynamical processes into an integrated system, and supervises the deployment and execution of that system.
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
Unlimited organizations, 3 enterprise SSO connections, role-based access control, and pro MFA included. Dev and prod tenants out of the box.
Auth0's B2B Essentials plan gives you everything you need to ship secure multi-tenant apps. Unlimited orgs, enterprise SSO, RBAC, audit log streaming, and higher auth and API limits included. Add on M2M tokens, enterprise MFA, or additional SSO connections as you scale.
The purpose of this program is to teach a computer to classify plants via their leaves. You just need to input the image of a leaf(acquired from scanner or camera), then the computer can tell you what kind of plant it is.
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.
An open-source package for analysis of neurophysiological data-- offline (vs real-time) processing of single-neuron spike trains or EEG data associated with behavior and memory processes. Currently MATLAB heavy, with some Windows specific code.