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Our goal is to build systems which write code automatically from the kinds of specifications humans can most easily provide, such as examples and natural language instruction.
Program synthesis by sketching
Solar-Lezama, A · 2008
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Programming with angelic nondeterminism
Bodik, R., Chandra, S., Galenson, J., Kimelman, D., Tung, N., Barman, S., and Rodarmor, C · 2010
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Automating string processing in spreadsheets using input-output examples
Gulwani, S · 2011
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Bootstrap learning via modular concept discovery
Dechter, E., Malmaud, J., Adams, R. P., and Tenenbaum, J. B · 2013
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A machine learning framework for programming by example
Menon, A., Tamuz, O., Gulwani, S., Lampson, B., and Kalai, A · 2013
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Adam: A method for stochastic optimization
Kingma, D. and Ba, J · 2014
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Synthesizing data structure transformations from input-output examples
Feser, J. K., Chaudhuri, S., and Dillig, I · 2015
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Human-level concept learning through probabilistic program induction
Lake, B. M., Salakhutdinov, R., and Tenenbaum, J. B · 2015
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Flashmeta: a framework for inductive program synthesis
Polozov, O. and Gulwani, S · 2015
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Sygus-comp 2016: Results and analysis
Alur, R., Fisman, D., Singh, R., and Solar-Lezama, A · 2016
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Deepcoder: Learning to write programs
Balog, M., Gaunt, A. L., Brockschmidt, M., Nowozin, S., and Tarlow, D · 2016
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Inference compilation and universal probabilistic programming
Le, T. A., Baydin, A. G., and Wood, F · 2016
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Parisotto, E., Mohamed, A.-r., Singh, R., Li, L., Zhou, D., and Kohli, P · 2016
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Stochastic program optimization
Schkufza, E., Sharma, R., and Aiken, A · 2016
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Programming with a differentiable forth interpreter
Bošnjak, M., Rocktäschel, T., Naradowsky, J., and Riedel, S · 2017
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Ain’t nobody got time for coding: Structure-aware program synthesis from natural language
Bednarek, J., Piaskowski, K., and Krawiec, K · 2018
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Leveraging grammar and reinforcement learning for neural program synthesis
Bunel, R., Hausknecht, M., Devlin, J., Singh, R., and Kohli, P · 2018
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Coarse-to-fine decoding for neural semantic parsing
Dong, L. and Lapata, M · 2018
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Learning libraries of subroutines for neurally–guided bayesian program learning
Ellis, K., Morales, L., Sablé-Meyer, M., Solar-Lezama, A., and Tenenbaum, J · 2018
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Neural-guided deductive search for real-time program synthesis from examples
Kalyan, A., Mohta, A., Polozov, O., Batra, D., Jain, P., and Gulwani, S · 2018
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Chen, X., Liu, C., and Song, D · 2017
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Robustfill: Neural program learning under noisy i/o
Devlin, J., Uesato, J., Bhupatiraju, S., Singh, R., Mohamed, A.-r., and Kohli, P · 2017
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Building machines that learn and think like people
Lake, B. M., Ullman, T. D., Tenenbaum, J. B., and Gershman, S. J · 2017
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Neural sketch learning for conditional program generation
Murali, V., Qi, L., Chaudhuri, S., and Jermaine, C · 2017
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Neural program search: Solving programming tasks from description and examples
Polosukhin, I. and Skidanov, A · 2018
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Improving neural program synthesis with inferred execution traces
Shin, R., Polosukhin, I., and Song, D · 2018
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Neural guided constraint logic programming for program synthesis
Zhang, L., Rosenblatt, G., Fetaya, E., Liao, R., Byrd, W., Might, M., Urtasun, R., and Zemel, R · 2018
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Automatic program synthesis of long programs with a learned garbage collector
Zohar, A. and Wolf, L · 2018
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