Neuroevolution of Bayesian Neural Networks

Since I first heard of Neuroevolution of Augmenting Topologies (or NEAT) by Kenneth Stanley I was hooked by it. How a metaheuristic (based on evolution) could produce increasingly complex models to solve problems. On the other hand, I was also interested in continuing learning about Bayesian Deep Learning (link to previous project). Therefore, I decided to mix things up and kill two birds with one stone.

Follow this links to know more:

• Github
• Report