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## TensorNEAT @ GECCO 2024 ## TensorNEAT @ GECCO 2024
TensorNEAT has been selected to recieve the **[GECCO 2024](https://gecco-2024.sigevo.org/HomePage) Best Paper Award** 🏆 TensorNEAT has been selected to recieve the **[GECCO 2024](https://gecco-2024.sigevo.org/HomePage) Best Paper Award** 🏆
Many thanks to everyone who is supporting TensorNEAT! Many thanks to everyone who is supporting TensorNEAT! We will remain committed to advancing TensorNEAT for future 'open-endedness'!
We will remain committed to advancing TensorNEAT for future 'open-endedness'!
## Introduction ## Introduction
TensorNEAT is a JAX-based libaray for NeuroEvolution of Augmenting Topologies (NEAT) algorithms, focused on harnessing GPU acceleration to enhance the efficiency of evolving neural network structures for complex tasks. Its core mechanism involves the tensorization of network topologies, enabling parallel processing and significantly boosting computational speed and scalability by leveraging modern hardware accelerators. TensorNEAT is compatible with the [EvoX](https://github.com/EMI-Group/evox/) framewrok. TensorNEAT is a JAX-based libaray for NeuroEvolution of Augmenting Topologies (NEAT) algorithms, focused on harnessing GPU acceleration to enhance the efficiency of evolving neural network structures for complex tasks. Its core mechanism involves the tensorization of network topologies, enabling parallel processing and significantly boosting computational speed and scalability by leveraging modern hardware accelerators. TensorNEAT is compatible with the [EvoX](https://github.com/EMI-Group/evox/) framewrok.