ICMLW 2018

7 papers

Automatically Constructing Compositional and Recursive Learners Michael Chang, Abhishek Gupta, Thomas Griffiths, Sergey Levine
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Execution-Guided Neural Program Decoding Chenglong Wang, Po-Sen Huang, Alex Polozov, Marc Brockschmidt, Rishabh Singh
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Improving the Neural GPU Architecture for Algorithm Learning Karlis Freivalds, Renars Liepins
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NAPS: Natural Program Synthesis Dataset Maksym Zavershynskyi, Alex Skidanov, Illia Polosukhin
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Program Language Translation Using a Grammar-Driven Tree-to-Tree Model Mehdi Drissi, Olivia Watkins, Aditya Khant, Vivaswat Ojha, Pedro Sandoval, Rakia Segev, Eric Weiner, Robert Keller
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Towards Mixed Optimization forReinforcement Learning with Program Synthesis Surya Bhupatiraju, Kumar Krishna Agrawal, Rishabh Singh
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Towards Neural Theorem Proving at Scale Pasquale Minervini, Matko Bošnjak, Tim Rocktäschel, Sebastian Riedel
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