This is a tutorial source code of the manuscript: "Digital computing through randomness and order in neural networks" Alexandre Pitti , Claudio Weidmann, and Mathias Quoy for the journal PNAS

This repo provides the necessary source code to simulate itinerant dynamics, that is, dynamics that randomly switch between attractor patterns, using a RNN implementation based on predictive coding.

Predictive coding algorithm for memory retrieval in RNNs. Based on a target sequence, we can infer the latent discrete representation (or class) that best predicts it.

A model using SOMs and active inference to learn a repertoire of simple motor trajectories

Example of learning, prediction and inference using a model of RNN based on predictive coding.

Example implementation of a two-layered network with predictive coding-based inference and learning.

A benchmark of online learning algorithms for RNNs in a continual learning setting. The models are evaluated on the task of incrementally learning a repertoire of 20 continuous sequences.

Introduction au langage Python3, à destination des doctorants et personnels de l'université.

This kit is for developing drone application with promethe NN simulator.

Regroupement de recettes singularity par le groupe MesoTech.

transfer in progress...

Modifications du logiciel Micmac développé par l'IGN.

transfer in progress...

Promethe Neural Networks Simulator

Basic Libraries for C