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Program synthesis is the task of automatically generating a program consistent with a specification.
Prow: A step toward automatic program writing
Richard J Waldinger and Richard CT Lee · 1969
Earlier work this paper cites.
Representations and modeling in problems of program formation
Saul Amarel · 1970
Earlier work this paper cites.
A methodology for lisp program construction from examples
Phillip D Summers · 1977
Earlier work this paper cites.
Karel the robot: a gentle introduction to the art of programming
Richard E Pattis · 1981
Earlier work this paper cites.
Inductive logic programming
Stephen Muggleton · 1991
Earlier work this paper cites.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams · 1992
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
Earlier work this paper cites.
Your wish is my command: Programming by example
Henry Lieberman · 2001
Earlier work this paper cites.
Learning programs: A hierarchical bayesian approach
Percy Liang, Michael I Jordan, and Dan Klein · 2010
Earlier work this paper cites.
Spreadsheet data manipulation using examples
Sumit Gulwani, William R Harris, and Rishabh Singh · 2012
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Speech recognition with deep recurrent neural networks
Alex Graves, Abdel-rahman Mohamed, and Geoffrey Hinton · 2013
Earlier work this paper cites.
Alex Graves, Greg Wayne, and Ivo Danihelka · 2014
Earlier work this paper cites.
Meta-interpretive learning: application to grammatical inference
Stephen H Muggleton, Dianhuan Lin, Niels Pahlavi, and Alireza Tamaddoni-Nezhad · 2014
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Learning to transduce with unbounded memory
Edward Grefenstette, Karl Moritz Hermann, Mustafa Suleyman, and Phil Blunsom · 2015
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Inferring algorithmic patterns with stack-augmented recurrent nets
Armand Joulin and Tomas Mikolov · 2015
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Adaptive neural compilation
Rudy R Bunel, Alban Desmaison, Pawan K Mudigonda, Pushmeet Kohli, and Philip Torr · 2016
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Terpret: A probabilistic programming language for program induction
Alexander L Gaunt, Marc Brockschmidt, Rishabh Singh, Nate Kushman, Pushmeet Kohli, Jonathan Taylor, and Daniel Tarlow · 2016
Cited alongside, same era.
Hybrid computing using a neural network with dynamic external memory
https://see.stanford.edu/Course/CS106A
Stanford CS106A course page · 2017
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http://hourofcode.codehs.com/
Hour of Code · 2017
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An actor-critic algorithm for sequence prediction
Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, Anirudh Goyal, Ryan Lowe, Joelle Pineau, Aaron Courville, and Yoshua Bengio · 2017
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Deepcoder: Learning to write programs
Matej Balog, Alexander L Gaunt, Marc Brockschmidt, Sebastian Nowozin, and Daniel Tarlow · 2017
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Making neural programming architectures generalize via recursion
Jonathon Cai, Richard Shin, and Dawn Song · 2017
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From language to programs: Bridging reinforcement learning and maximum marginal likelihood
Kelvin Guu, Panupong Pasupat, Evan Zheran Liu, and Percy Liang · 2017
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Sequence level training with recurrent neural networks
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Scott Reed and Nando de Freitas · 2016
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Sequence-to-sequence learning as beam-search optimization
Sam Wiseman and Alexander M Rush · 2016
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Inferring and executing programs for visual reasoning
Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Judy Hoffman, Fei-Fei Li, C. Lawrence Zitnick, and Ross B. Girshick · 2017
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Grammar variational autoencoder
Matt J Kusner, Brooks Paige, and José Miguel Hernández-Lobato · 2017
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Neural program lattices
Chengtao Li, Daniel Tarlow, Alexander L. Gaunt, Marc Brockschmidt, and Nate Kushman · 2017
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Neuro-symbolic program synthesis
Emilio Parisotto, Abdelrahman Mohamed, Rishabh Singh, Lihong Li, Denny Zhou, and Pushmeet Kohli · 2017
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Programming with a differentiable forth interpreter
Sebastian Riedel, Matko Bosnjak, and Tim Rocktäschel · 2017
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A syntactic neural model for general-purpose code generation
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