Taller de Adversarial Machine Learning

This project focuses on the implementation of inverting I-JEAP, a new architecture designed to simulate human intelligence through self-supervised learning. Our goal is to invert the embeddings to demonstrate that such architectures can be vulnerable to inversion attacks