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## TensorNEAT @ GECCO 2024
🎉🎉TensorNEAT has been awarded the **[GECCO 2024](https://gecco-2024.sigevo.org/HomePage) Best Paper** ! 🎉🎉
Many thanks to everyone who voted for us and supported TensorNEAT! We will continue to maintain the TensorNEAT project and look forward to advancing Neuroevolution together with you all!
Many thanks to everyone who has been supporting TensorNEAT! We will remain committed to advancing TensorNEAT for future 'open-endedness'!
## 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.