Unsupervised Concepts Extraction in Neural Networks

Défense de mémoire de Sacha Corbugy et Thibaut Septon

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Recently, the domain of Explainable Artificial Intelligence (XAI) saw the advent of Testing with CAV (TCAV). Although very practical as they allow to check the importance of a concept in the decision making of a neural network, they pose the prerequisite of knowing the concept at stake and having a dedicated dataset.

In order to remedy this, a method is proposed to obtain an overview of the different concepts that are important in the decision making process of a neural network.

The idea beneath the proposed method is to compare and label the neural network instances based on their activation at a given layer inside the network itself.

Using two different kinds of neural network, an image classifier and a game agent, the method is tested to see if an unsupervised extraction of concepts is possible.

Contact : Isabelle Daelman - isabelle.daelman@unamur.be
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