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Deep Distilling: automated code generation using explainable deep learning
On a diverse set of problems involving arithmetic, computer vision, and optimization, we show that deep distilling generates concise code that generalizes out-of-distribution to solve problems orders-of-magnitude larger and more complex than the training data.
A neural network model of perception and reasoning
How perception and reasoning arise from neuronal network activity is poorly understood.
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