The LIBRARY is a C++/Python implementation of the variational building block framework introduced in our papers. The framework allows easy learning of a wide variety of models using variational Bayesian learning
* Lightweight backpropagation neural network.
* This a lightweight LIBRARY implementating a neural network for use
* in C and C++ programs. It is intended for use in applications that
* just happen to need a simply neural network and do not want to use
* needlessly complex neural network libraries. It features multilayer
* feedforward perceptron neural networks, sigmoidal activation function
* with bias, backpropagation training with settable learning rate and
* momentum, and backpropagation training in batches.
neural network utility is a Neural Networks LIBRARY for the
C++ Programmer. It is entirely object oriented and focuses
on reducing tedious and confusing problems of programming neural networks.
By this I mean that network layers are easily defined. An
entire multi-layer network can be created in a few lines, and
trained with two functions. Layers can be connected to one another
easily and painlessly.
It is a GPL basic windowing LIBRARY created specifically for windows and uses only basic win32 services. It currently compiles under Borland C++ and Microsoft C++, other compilers are untested.It provides a common windows toolkit for al c++ environments.
