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In our paper "Can Neural Networks Distinguish High-school Level Mathematical Concepts?" we evaluate the ability of various neural networks to classify the relationship between two mathematical expressions. For example, two expressions can be equivalent or one could be a derivative of the other. We show that neural networks are able to learn the underlying mathematical patterns and outperform rule-based systems.
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