We present NeuralOperator, an open-source Python library for operator learning. Neural operators generalize neural networks to maps between function spaces instead of finite-dimensional Euclidean spaces. They can be trained and inferenced on input and output functions given at various discretizations, satisfying a discretization convergence properties. Built on top of PyTorch, NeuralOperator provides all the tools for training and deploying neural operator models, as well as developing new ones, in a high-quality, tested, open-source package. It combines cutting-edge models and customizability with a gentle learning curve and simple user interface for newcomers.

翻译：我们提出了NeuralOperator，一个用于算子学习的开源Python库。神经算子将神经网络推广为函数空间之间的映射，而非有限维欧几里得空间之间的映射。它们可以在不同离散化程度下给定的输入和输出函数上进行训练和推理，并满足离散化收敛特性。NeuralOperator基于PyTorch构建，在一个高质量、经过测试的开源包中，提供了训练和部署神经算子模型以及开发新模型所需的所有工具。它将前沿模型与可定制性相结合，并为新用户提供了平缓的学习曲线和简洁的用户界面。