Can neuro-evolution of augmenting topologies (NEAT) neural networks be built in TensorFlow? I am making a machine learning program for time series data analysis and using NEAT could help the work. I started to learn TensorFlow not long ago but it seems that the computational graphs in TensorFlow are usually fixed. Is there tools in TensorFlow to help build a dynamically evolving neural network? Or something like PyTorch would be a better alternative? Thanks.
Check this implementation in TensorFlow Eager: https://github.com/crisbodnar/TensorFlow-NEAT