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TensorNEAT: Tensorized NeuroEvolution of Augmenting Topologies for GPU Acceleration

TensorNEAT is a powerful tool that utilizes JAX to implement the NEAT (NeuroEvolution of Augmenting Topologies) algorithm. It provides support for parallel execution of tasks such as forward network computation, mutation, and crossover at the population level.

Description
MEND: Modular Evolutionary Neuroduplication — TensorNEAT fork with module duplication operator
Readme 36 MiB
Languages
Python 54.3%
Jupyter Notebook 45.7%