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DeepXDE is an open-source library designed for scientific machine learning and physics-informed neural networks. It simplifies the implementation of deep learning models for solving differential equations, both ordinary and partial, by incorporating domain knowledge directly into the learning process. With its flexible and user-friendly API, DeepXDE supports a wide range of applications in science and engineering, enabling researchers to build accurate and efficient models for complex physical systems.
