NEURECO : AUTOMATIC PARSIMONIOUS NEURAL NETWORKS GENERATION

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NeurEco introduces a new generation of neural networks, based on parsimony. Using NeurEco’s parsimonious approach, the resources required for implementing artificial intelligence are reduced by several orders of magnitude. This includes reduction in the necessary amount of learning data, computing resources, development time, and energy consumption.

NeurEco is an ANN (artificial neural network) factory. It generates parsimonious ANN models automatically, using only the learning data provided by the user.

Note that in the near future, a new convolution-based family of add-ons will be added to the product to handle the problems where the inputs are represented by data on regular grids (for example regression problems with images as inputs).

NeurEco can be used from the command line or via a user-friendly graphical interface and can accept the following data formats: csv, npy and MATLAB matfile.
It comes with an additional API for Python3, making it much easier to interact with standard AI environments.
It allows to export the generated models to C, ONNX or FMU.

Please find our documentation here

Neural models for regression, classification, and compression of tabular data.

Recurrent models for highly accurate long-term dynamic predictions.

Optimal solution for the design of antennas and resonant structures.

Several types of licenses are available to meet your usage needs: single-user / floating ; annual / perpetual.