RobustFill: Neural Program Learning under Noisy I/O

ICML 2017 Jacob DevlinJonathan UesatoSurya BhupatirajuRishabh SinghAbdel-rahman MohamedPushmeet Kohli

The problem of automatically generating a computer program from some specification has been studied since the early days of AI. Recently, two competing approaches for automatic program learning have received significant attention: (1) neural program synthesis, where a neural network is conditioned on input/output (I/O) examples and learns to generate a program, and (2) neural program induction, where a neural network generates new outputs directly using a latent program representation... (read more)

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