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This project is a quest for conscious artificial intelligence. A number of prototypes will be developed as the project progresses.
This project has 2 subprojects:
Object Pascal based CAI NEURAL API - https://github.com/joaopauloschuler/neural-api
Python based K-CAI NEURAL API - https://github.com/joaopauloschuler/k-neural-api
A video from the first prototype has been made:
http://www.youtube.com/watch?v=qH-IQgYy9zg
Above video shows a popperian agent collecting mining ore from 3...
Multiscale Neuroscience and Systems Biology Simulator
Moose is the core of a modern software platform for the simulation of neural systems ranging from subcellular components and biochemical reactions to complex models of single neurons, large networks, and systems-level processes.
We have moved Github.com. This should be your source for the latest version of the code.
Mullpy is a machine-learning library that mainly aim to solve multi-label problems. It is classifier independent, has many ensemble capabilities (diversity methods like bagging, random subspaces, etc.) and automated results presentation (Excel, images as ROC or class-separated info, etc.). It is fully configurable. At the moment supports Neural Networks and classifiers defined in files. It is working on python3.3.
NeMo is a high-performance spiking neural network simulator which simulates networks of Izhikevich neurons on CUDA-enabled GPUs. NeMo is a C++ class library, with additional interfaces for pure C, Python, and Matlab.
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This is a c-library that provides tools for advanced
analysis of electrophysiological data. It features
denoising, unsupervised classification, time-frequency
analysis, phase-space analysis, neural networks, time-warping and
more.
Brian is a new simulator for spiking neural networks available on almost all platforms. The motivation for this project is that a simulator should not only save the time of processors, but also the time of scientists.