Learning to Complete Code with Sketches
Daya Guo, Alexey Svyatkovskiy, Jian Yin, Nan Duan, Marc Brockschmidt, Miltos Allamanis
ICLR 2022 | April 2022
Deep Program Understanding
Teaching machines to understand complex algorithms
Publications
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-
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HEAT: Hyperedge Attention Networks
Dobrik Georgiev, Marc Brockschmidt, Miltos Allamanis
January 2022
-
-
-
Self-Supervised Bug Detection and Repair
Miltos Allamanis, Henry Jackson-Flux, Marc Brockschmidt
NeurIPS 2021 | May 2021
-
Copy that! Editing Sequences by Copying Spans
Sheena Panthaplackel, Miltos Allamanis, Marc Brockschmidt
AAAI | January 2021
-
-
-
Typilus: Neural Type Hints
Miltos Allamanis, Earl T. Barr, Soline Ducousso, Zheng Gao
2020 Programming Language Design and Implementation | June 2020
-
Fast and Memory-Efficient Neural Code Completion
Alexey Svyatkovskiy, Sebastian Lee, Anna Hadjitofi, Maik Riechert, Juliana Vicente Franco, Miltos Allamanis
Mining Software Repositories | April 2020
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-
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DIRE: a neural approach to decompiled identifier naming
Jeremy Lacomis, Pengcheng Yin, Edward J. Schwartz, Miltos Allamanis, Claire Le Goues, Graham Neubig, Bogdan Vasilescu
2019 Automated Software Engineering | November 2019
-
The adverse effects of code duplication in machine learning models of code
Miltos Allamanis
2019 SIGPLAN symposium on New ideas, new paradigms, and reflections on programming and software | October 2019
DOI Publication Publication Publication Publication Publication
-
CodeSearchNet Challenge: Evaluating the State of Semantic Code Search.
Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit, Miltos Allamanis, Marc Brockschmidt
MSR-TR-2019-45 | September 2019
Published by Microsoft
-
Generative Code Modeling with Graphs
Marc Brockschmidt, Miltos Allamanis, Alex Gaunt, Alex Polozov
7th International Conference on Learning Representations | May 2019
-
Learning to Represent Edits
Pengcheng Yin, Graham Neubig, Miltiadis Allamanis, Marc Brockschmidt, Alexander Gaunt
ICLR 2019 | May 2019
arXiv:1810.13337 [cs.LG]
-
-
-
Constrained Graph Variational Autoencoders for Molecule Design
Qi Liu, Miltos Allamanis, Marc Brockschmidt, Alexander Gaunt
NIPS 2018 | December 2018
-
Deep learning type inference
Vincent J. Hellendoorn, Christian Bird, Earl T. Barr, Miltos Allamanis
Foundations of Software Engineering | October 2018
-
RefiNym: using names to refine types
Santanu Kumar Dash, Miltos Allamanis, Earl T. Barr
Foundations of Software Engineering | October 2018
-
Structured Neural Summarization
Patrick Fernandes, Miltos Allamanis, Marc Brockschmidt
2018 International Conference on Learning Representations | September 2018
-
Robust Text-to-SQL Generation with Execution-Guided Decoding
Chenglong Wang, Kedar Tatwawadi, Marc Brockschmidt, Po-Sen Huang, Yi Mao, Oleksandr Polozov, Rishabh Singh
September 2018
arXiv | September 2018
-
A Survey of Machine Learning for Big Code and Naturalness
Miltos Allamanis, Earl T. Barr, Premkumar Devanbu, Charles Sutton
ACM Computing Surveys | July 2018, Vol 51(4): pp. 81
-
-
-
Semantics-aware Program Sampling
Pratiksha Thaker, Daniel Tarlow, Marc Brockschmidt, Alexander Gaunt
MSR-TR-2017-47 | November 2017
-
Graph Partition Neural Networks for Semi-Supervised Classification
Renjie Liao, Marc Brockschmidt (mabrocks), Daniel Tarlow, Alexander Gaunt, Raquel Urtasun, Richard S. Zemel
MSR-TR-2017-46 | November 2017
Published by Microsoft
-
Learning to Represent Programs with Graphs
Miltos Allamanis, Marc Brockschmidt, Mahmoud Khademi
International Conference on Learning Representations 2018 | November 2017
-
Pointing Out SQL Queries From Text
Chenglong Wang, Marc Brockschmidt, Rishabh Singh
MSR-TR-2017-45 | November 2017
-
Differentiable Programs with Neural Libraries
Alexander Gaunt, Marc Brockschmidt, Nate Kushman, Daniel Tarlow
Proceedings of ICML’17 | July 2017
-
Learning Shape Analysis
Marc Brockschmidt, Yuxin Chen, Pushmeet Kohli, Siddharth Krishna, Daniel Tarlow
Proceedings of SAS’17 | July 2017
-
SmartPaste: Learning to Adapt Source Code
Miltos Allamanis, Marc Brockschmidt
May 2017
arXiv | May 2017
-
Neural Program Lattices
Chengtao Li, Daniel Tarlow, Alexander Gaunt, Marc Brockschmidt, Nate Kushman
Proceedings of ICLR’17 | March 2017
-
DeepCoder: Learning to Write Programs
Matej Balog, Alexander Gaunt, Marc Brockschmidt, Sebastian Nowozin, Daniel Tarlow
Proceedings of ICLR’17 | March 2017
-
Differentiable Functional Program Interpreters
John K. Feser, Marc Brockschmidt, Alexander Gaunt, Daniel Tarlow
March 2017
-
-
-
Mining Semantic Loop Idioms from Big Code
Miltiadis Allamanis, Earl T. Barr, Christian Bird, Premkumar Devanbu, Mark Marron, Charles Sutton
MSR-TR-2016-1116 | November 2016
-
TerpreT: A Probabilistic Programming Language for Program Induction
Alexander L. Gaunt, Marc Brockschmidt, Rishabh Singh, Nate Kushman, Pushmeet Kohli, Daniel Tarlow
August 2016
arXiv | August 2016
Best paper at NIPS Workshop on Neural Abstract Machines and Program Induction (NAMPI 2016)
-
Gated Graph Sequence Neural Networks
Yujia Li, Richard Zemel, Marc Brockschmidt, Daniel Tarlow
Proceedings of ICLR’16 | April 2016
-
SWIM: Synthesizing What I Mean
Mukund Raghothaman, Yi Wei, Youssef Hamadi
ICSE 2016 | February 2016
-
A Convolutional Attention Network for Extreme Summarization of Source Code
Miltos Allamanis, Hao Peng, Charles Sutton
International Conference on Machine Learning | February 2016
-
-
-
Suggesting accurate method and class names
Miltos Allamanis, Earl T. Barr, Christian Bird, Charles Sutton
Foundations of Software Engineering | August 2015
-
Bimodal Modelling of Source Code and Natural Language
Miltos Allamanis, Daniel Tarlow, Andy Gordon, Yi Wei
International Conference on Machine Learning | August 2015
-
Learning to Decipher the Heap for Program Verification
Marc Brockschmidt, Yuxin Chen, Byron Cook, Pushmeet Kohli, Daniel Tarlow
ICML 2015 Proceedings of the Constructive Machine Learning | July 2015
-
-
-
Learning Natural Coding Conventions
Miltiadis Allamanis, Earl T. Barr, Christian Bird, Charles Sutton
Proceedings of the ACM SigSoft Symposium on Foundations of Software Engineering | November 2014
-
Structured Generative Models of Natural Source Code
Chris J. Maddison, Daniel Tarlow
The 31st International Conference on Machine Learning (ICML) | June 2014
-
-
-
Learning to Complete Code with Sketches
Daya Guo, Alexey Svyatkovskiy, Jian Yin, Nan Duan, Marc Brockschmidt, Miltos Allamanis
ICLR 2022 | April 2022
-
HEAT: Hyperedge Attention Networks
Dobrik Georgiev, Marc Brockschmidt, Miltos Allamanis
January 2022
-
Self-Supervised Bug Detection and Repair
Miltos Allamanis, Henry Jackson-Flux, Marc Brockschmidt
NeurIPS 2021 | May 2021
-
Copy that! Editing Sequences by Copying Spans
Sheena Panthaplackel, Miltos Allamanis, Marc Brockschmidt
AAAI | January 2021
-
Typilus: Neural Type Hints
Miltos Allamanis, Earl T. Barr, Soline Ducousso, Zheng Gao
2020 Programming Language Design and Implementation | June 2020
-
Fast and Memory-Efficient Neural Code Completion
Alexey Svyatkovskiy, Sebastian Lee, Anna Hadjitofi, Maik Riechert, Juliana Vicente Franco, Miltos Allamanis
Mining Software Repositories | April 2020
-
The adverse effects of code duplication in machine learning models of code
Miltos Allamanis
2019 SIGPLAN symposium on New ideas, new paradigms, and reflections on programming and software | October 2019
DOI Publication Publication Publication Publication Publication
-
Generative Code Modeling with Graphs
Marc Brockschmidt, Miltos Allamanis, Alex Gaunt, Alex Polozov
7th International Conference on Learning Representations | May 2019
-
Learning to Represent Edits
Pengcheng Yin, Graham Neubig, Miltiadis Allamanis, Marc Brockschmidt, Alexander Gaunt
ICLR 2019 | May 2019
arXiv:1810.13337 [cs.LG]
-
Constrained Graph Variational Autoencoders for Molecule Design
Qi Liu, Miltos Allamanis, Marc Brockschmidt, Alexander Gaunt
NIPS 2018 | December 2018
-
Structured Neural Summarization
Patrick Fernandes, Miltos Allamanis, Marc Brockschmidt
2018 International Conference on Learning Representations | September 2018
-
Robust Text-to-SQL Generation with Execution-Guided Decoding
Chenglong Wang, Kedar Tatwawadi, Marc Brockschmidt, Po-Sen Huang, Yi Mao, Oleksandr Polozov, Rishabh Singh
September 2018
arXiv | September 2018
-
A Survey of Machine Learning for Big Code and Naturalness
Miltos Allamanis, Earl T. Barr, Premkumar Devanbu, Charles Sutton
ACM Computing Surveys | July 2018, Vol 51(4): pp. 81
-
Semantics-aware Program Sampling
Pratiksha Thaker, Daniel Tarlow, Marc Brockschmidt, Alexander Gaunt
MSR-TR-2017-47 | November 2017
-
Graph Partition Neural Networks for Semi-Supervised Classification
Renjie Liao, Marc Brockschmidt (mabrocks), Daniel Tarlow, Alexander Gaunt, Raquel Urtasun, Richard S. Zemel
MSR-TR-2017-46 | November 2017
Published by Microsoft
-
Pointing Out SQL Queries From Text
Chenglong Wang, Marc Brockschmidt, Rishabh Singh
MSR-TR-2017-45 | November 2017
-
Learning to Represent Programs with Graphs
Miltos Allamanis, Marc Brockschmidt, Mahmoud Khademi
International Conference on Learning Representations 2018 | November 2017
-
Differentiable Programs with Neural Libraries
Alexander Gaunt, Marc Brockschmidt, Nate Kushman, Daniel Tarlow
Proceedings of ICML’17 | July 2017
-
Learning Shape Analysis
Marc Brockschmidt, Yuxin Chen, Pushmeet Kohli, Siddharth Krishna, Daniel Tarlow
Proceedings of SAS’17 | July 2017
-
SmartPaste: Learning to Adapt Source Code
Miltos Allamanis, Marc Brockschmidt
May 2017
arXiv | May 2017
-
Neural Program Lattices
Chengtao Li, Daniel Tarlow, Alexander Gaunt, Marc Brockschmidt, Nate Kushman
Proceedings of ICLR’17 | March 2017
-
Differentiable Functional Program Interpreters
John K. Feser, Marc Brockschmidt, Alexander Gaunt, Daniel Tarlow
March 2017
-
DeepCoder: Learning to Write Programs
Matej Balog, Alexander Gaunt, Marc Brockschmidt, Sebastian Nowozin, Daniel Tarlow
Proceedings of ICLR’17 | March 2017
-
Mining Semantic Loop Idioms from Big Code
Miltiadis Allamanis, Earl T. Barr, Christian Bird, Premkumar Devanbu, Mark Marron, Charles Sutton
MSR-TR-2016-1116 | November 2016
-
TerpreT: A Probabilistic Programming Language for Program Induction
Alexander L. Gaunt, Marc Brockschmidt, Rishabh Singh, Nate Kushman, Pushmeet Kohli, Daniel Tarlow
August 2016
arXiv | August 2016
Best paper at NIPS Workshop on Neural Abstract Machines and Program Induction (NAMPI 2016)
-
Gated Graph Sequence Neural Networks
Yujia Li, Richard Zemel, Marc Brockschmidt, Daniel Tarlow
Proceedings of ICLR’16 | April 2016
-
SWIM: Synthesizing What I Mean
Mukund Raghothaman, Yi Wei, Youssef Hamadi
ICSE 2016 | February 2016
-
A Convolutional Attention Network for Extreme Summarization of Source Code
Miltos Allamanis, Hao Peng, Charles Sutton
International Conference on Machine Learning | February 2016
-
Bimodal Modelling of Source Code and Natural Language
Miltos Allamanis, Daniel Tarlow, Andy Gordon, Yi Wei
International Conference on Machine Learning | August 2015
-
Structured Generative Models of Natural Source Code
Chris J. Maddison, Daniel Tarlow
The 31st International Conference on Machine Learning (ICML) | June 2014
-
-
-
Learning to Complete Code with Sketches
Daya Guo, Alexey Svyatkovskiy, Jian Yin, Nan Duan, Marc Brockschmidt, Miltos Allamanis
ICLR 2022 | April 2022
-
HEAT: Hyperedge Attention Networks
Dobrik Georgiev, Marc Brockschmidt, Miltos Allamanis
January 2022
-
Self-Supervised Bug Detection and Repair
Miltos Allamanis, Henry Jackson-Flux, Marc Brockschmidt
NeurIPS 2021 | May 2021
-
Typilus: Neural Type Hints
Miltos Allamanis, Earl T. Barr, Soline Ducousso, Zheng Gao
2020 Programming Language Design and Implementation | June 2020
-
Fast and Memory-Efficient Neural Code Completion
Alexey Svyatkovskiy, Sebastian Lee, Anna Hadjitofi, Maik Riechert, Juliana Vicente Franco, Miltos Allamanis
Mining Software Repositories | April 2020
-
DIRE: a neural approach to decompiled identifier naming
Jeremy Lacomis, Pengcheng Yin, Edward J. Schwartz, Miltos Allamanis, Claire Le Goues, Graham Neubig, Bogdan Vasilescu
2019 Automated Software Engineering | November 2019
-
The adverse effects of code duplication in machine learning models of code
Miltos Allamanis
2019 SIGPLAN symposium on New ideas, new paradigms, and reflections on programming and software | October 2019
DOI Publication Publication Publication Publication Publication
-
CodeSearchNet Challenge: Evaluating the State of Semantic Code Search.
Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit, Miltos Allamanis, Marc Brockschmidt
MSR-TR-2019-45 | September 2019
Published by Microsoft
-
Generative Code Modeling with Graphs
Marc Brockschmidt, Miltos Allamanis, Alex Gaunt, Alex Polozov
7th International Conference on Learning Representations | May 2019
-
Learning to Represent Edits
Pengcheng Yin, Graham Neubig, Miltiadis Allamanis, Marc Brockschmidt, Alexander Gaunt
ICLR 2019 | May 2019
arXiv:1810.13337 [cs.LG]
-
Constrained Graph Variational Autoencoders for Molecule Design
Qi Liu, Miltos Allamanis, Marc Brockschmidt, Alexander Gaunt
NIPS 2018 | December 2018
-
Deep learning type inference
Vincent J. Hellendoorn, Christian Bird, Earl T. Barr, Miltos Allamanis
Foundations of Software Engineering | October 2018
-
RefiNym: using names to refine types
Santanu Kumar Dash, Miltos Allamanis, Earl T. Barr
Foundations of Software Engineering | October 2018
-
Semantics-aware Program Sampling
Pratiksha Thaker, Daniel Tarlow, Marc Brockschmidt, Alexander Gaunt
MSR-TR-2017-47 | November 2017
-
Pointing Out SQL Queries From Text
Chenglong Wang, Marc Brockschmidt, Rishabh Singh
MSR-TR-2017-45 | November 2017
-
Learning to Represent Programs with Graphs
Miltos Allamanis, Marc Brockschmidt, Mahmoud Khademi
International Conference on Learning Representations 2018 | November 2017
-
Differentiable Programs with Neural Libraries
Alexander Gaunt, Marc Brockschmidt, Nate Kushman, Daniel Tarlow
Proceedings of ICML’17 | July 2017
-
Learning Shape Analysis
Marc Brockschmidt, Yuxin Chen, Pushmeet Kohli, Siddharth Krishna, Daniel Tarlow
Proceedings of SAS’17 | July 2017
-
SmartPaste: Learning to Adapt Source Code
Miltos Allamanis, Marc Brockschmidt
May 2017
arXiv | May 2017
-
Neural Program Lattices
Chengtao Li, Daniel Tarlow, Alexander Gaunt, Marc Brockschmidt, Nate Kushman
Proceedings of ICLR’17 | March 2017
-
Differentiable Functional Program Interpreters
John K. Feser, Marc Brockschmidt, Alexander Gaunt, Daniel Tarlow
March 2017
-
DeepCoder: Learning to Write Programs
Matej Balog, Alexander Gaunt, Marc Brockschmidt, Sebastian Nowozin, Daniel Tarlow
Proceedings of ICLR’17 | March 2017
-
Mining Semantic Loop Idioms from Big Code
Miltiadis Allamanis, Earl T. Barr, Christian Bird, Premkumar Devanbu, Mark Marron, Charles Sutton
MSR-TR-2016-1116 | November 2016
-
TerpreT: A Probabilistic Programming Language for Program Induction
Alexander L. Gaunt, Marc Brockschmidt, Rishabh Singh, Nate Kushman, Pushmeet Kohli, Daniel Tarlow
August 2016
arXiv | August 2016
Best paper at NIPS Workshop on Neural Abstract Machines and Program Induction (NAMPI 2016)
-
SWIM: Synthesizing What I Mean
Mukund Raghothaman, Yi Wei, Youssef Hamadi
ICSE 2016 | February 2016
-
Suggesting accurate method and class names
Miltos Allamanis, Earl T. Barr, Christian Bird, Charles Sutton
Foundations of Software Engineering | August 2015
-
Bimodal Modelling of Source Code and Natural Language
Miltos Allamanis, Daniel Tarlow, Andy Gordon, Yi Wei
International Conference on Machine Learning | August 2015
-
Learning to Decipher the Heap for Program Verification
Marc Brockschmidt, Yuxin Chen, Byron Cook, Pushmeet Kohli, Daniel Tarlow
ICML 2015 Proceedings of the Constructive Machine Learning | July 2015
-
Learning Natural Coding Conventions
Miltiadis Allamanis, Earl T. Barr, Christian Bird, Charles Sutton
Proceedings of the ACM SigSoft Symposium on Foundations of Software Engineering | November 2014
-
-
-
Learning to Complete Code with Sketches
Daya Guo, Alexey Svyatkovskiy, Jian Yin, Nan Duan, Marc Brockschmidt, Miltos Allamanis
ICLR 2022 | April 2022
-
Self-Supervised Bug Detection and Repair
Miltos Allamanis, Henry Jackson-Flux, Marc Brockschmidt
NeurIPS 2021 | May 2021
-
Copy that! Editing Sequences by Copying Spans
Sheena Panthaplackel, Miltos Allamanis, Marc Brockschmidt
AAAI | January 2021
-
Typilus: Neural Type Hints
Miltos Allamanis, Earl T. Barr, Soline Ducousso, Zheng Gao
2020 Programming Language Design and Implementation | June 2020
-
Fast and Memory-Efficient Neural Code Completion
Alexey Svyatkovskiy, Sebastian Lee, Anna Hadjitofi, Maik Riechert, Juliana Vicente Franco, Miltos Allamanis
Mining Software Repositories | April 2020
-
DIRE: a neural approach to decompiled identifier naming
Jeremy Lacomis, Pengcheng Yin, Edward J. Schwartz, Miltos Allamanis, Claire Le Goues, Graham Neubig, Bogdan Vasilescu
2019 Automated Software Engineering | November 2019
-
The adverse effects of code duplication in machine learning models of code
Miltos Allamanis
2019 SIGPLAN symposium on New ideas, new paradigms, and reflections on programming and software | October 2019
DOI Publication Publication Publication Publication Publication
-
Generative Code Modeling with Graphs
Marc Brockschmidt, Miltos Allamanis, Alex Gaunt, Alex Polozov
7th International Conference on Learning Representations | May 2019
-
Learning to Represent Edits
Pengcheng Yin, Graham Neubig, Miltiadis Allamanis, Marc Brockschmidt, Alexander Gaunt
ICLR 2019 | May 2019
arXiv:1810.13337 [cs.LG]
-
Constrained Graph Variational Autoencoders for Molecule Design
Qi Liu, Miltos Allamanis, Marc Brockschmidt, Alexander Gaunt
NIPS 2018 | December 2018
-
Deep learning type inference
Vincent J. Hellendoorn, Christian Bird, Earl T. Barr, Miltos Allamanis
Foundations of Software Engineering | October 2018
-
RefiNym: using names to refine types
Santanu Kumar Dash, Miltos Allamanis, Earl T. Barr
Foundations of Software Engineering | October 2018
-
Structured Neural Summarization
Patrick Fernandes, Miltos Allamanis, Marc Brockschmidt
2018 International Conference on Learning Representations | September 2018
-
Learning to Represent Programs with Graphs
Miltos Allamanis, Marc Brockschmidt, Mahmoud Khademi
International Conference on Learning Representations 2018 | November 2017
-
Differentiable Programs with Neural Libraries
Alexander Gaunt, Marc Brockschmidt, Nate Kushman, Daniel Tarlow
Proceedings of ICML’17 | July 2017
-
Learning Shape Analysis
Marc Brockschmidt, Yuxin Chen, Pushmeet Kohli, Siddharth Krishna, Daniel Tarlow
Proceedings of SAS’17 | July 2017
-
Neural Program Lattices
Chengtao Li, Daniel Tarlow, Alexander Gaunt, Marc Brockschmidt, Nate Kushman
Proceedings of ICLR’17 | March 2017
-
Differentiable Functional Program Interpreters
John K. Feser, Marc Brockschmidt, Alexander Gaunt, Daniel Tarlow
March 2017
-
DeepCoder: Learning to Write Programs
Matej Balog, Alexander Gaunt, Marc Brockschmidt, Sebastian Nowozin, Daniel Tarlow
Proceedings of ICLR’17 | March 2017
-
Gated Graph Sequence Neural Networks
Yujia Li, Richard Zemel, Marc Brockschmidt, Daniel Tarlow
Proceedings of ICLR’16 | April 2016
-
SWIM: Synthesizing What I Mean
Mukund Raghothaman, Yi Wei, Youssef Hamadi
ICSE 2016 | February 2016
-
A Convolutional Attention Network for Extreme Summarization of Source Code
Miltos Allamanis, Hao Peng, Charles Sutton
International Conference on Machine Learning | February 2016
-
Suggesting accurate method and class names
Miltos Allamanis, Earl T. Barr, Christian Bird, Charles Sutton
Foundations of Software Engineering | August 2015
-
Bimodal Modelling of Source Code and Natural Language
Miltos Allamanis, Daniel Tarlow, Andy Gordon, Yi Wei
International Conference on Machine Learning | August 2015
-
Learning to Decipher the Heap for Program Verification
Marc Brockschmidt, Yuxin Chen, Byron Cook, Pushmeet Kohli, Daniel Tarlow
ICML 2015 Proceedings of the Constructive Machine Learning | July 2015
-
Learning Natural Coding Conventions
Miltiadis Allamanis, Earl T. Barr, Christian Bird, Charles Sutton
Proceedings of the ACM SigSoft Symposium on Foundations of Software Engineering | November 2014
-
Structured Generative Models of Natural Source Code
Chris J. Maddison, Daniel Tarlow
The 31st International Conference on Machine Learning (ICML) | June 2014
-
-
-
HEAT: Hyperedge Attention Networks
Dobrik Georgiev, Marc Brockschmidt, Miltos Allamanis
January 2022
-
-
-
Robust Text-to-SQL Generation with Execution-Guided Decoding
Chenglong Wang, Kedar Tatwawadi, Marc Brockschmidt, Po-Sen Huang, Yi Mao, Oleksandr Polozov, Rishabh Singh
September 2018
arXiv | September 2018
-
SmartPaste: Learning to Adapt Source Code
Miltos Allamanis, Marc Brockschmidt
May 2017
arXiv | May 2017
-
TerpreT: A Probabilistic Programming Language for Program Induction
Alexander L. Gaunt, Marc Brockschmidt, Rishabh Singh, Nate Kushman, Pushmeet Kohli, Daniel Tarlow
August 2016
arXiv | August 2016
Best paper at NIPS Workshop on Neural Abstract Machines and Program Induction (NAMPI 2016)
-
-
-
A Survey of Machine Learning for Big Code and Naturalness
Miltos Allamanis, Earl T. Barr, Premkumar Devanbu, Charles Sutton
ACM Computing Surveys | July 2018, Vol 51(4): pp. 81
-
-
-
CodeSearchNet Challenge: Evaluating the State of Semantic Code Search.
Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit, Miltos Allamanis, Marc Brockschmidt
MSR-TR-2019-45 | September 2019
Published by Microsoft
-
Semantics-aware Program Sampling
Pratiksha Thaker, Daniel Tarlow, Marc Brockschmidt, Alexander Gaunt
MSR-TR-2017-47 | November 2017
-
Graph Partition Neural Networks for Semi-Supervised Classification
Renjie Liao, Marc Brockschmidt (mabrocks), Daniel Tarlow, Alexander Gaunt, Raquel Urtasun, Richard S. Zemel
MSR-TR-2017-46 | November 2017
Published by Microsoft
-
Pointing Out SQL Queries From Text
Chenglong Wang, Marc Brockschmidt, Rishabh Singh
MSR-TR-2017-45 | November 2017
-
Mining Semantic Loop Idioms from Big Code
Miltiadis Allamanis, Earl T. Barr, Christian Bird, Premkumar Devanbu, Mark Marron, Charles Sutton
MSR-TR-2016-1116 | November 2016
-