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David Bieber
David Bieber
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Show your work: Scratchpads for intermediate computation with language models
M Nye, AJ Andreassen, G Gur-Ari, H Michalewski, J Austin, D Bieber, ...
arXiv preprint arXiv:2112.00114, 2021
4322021
Global relational models of source code
VJ Hellendoorn, C Sutton, R Singh, P Maniatis, D Bieber
International conference on learning representations, 2019
2532019
Neural program repair by jointly learning to localize and repair
M Vasic, A Kanade, P Maniatis, D Bieber, R Singh
arXiv preprint arXiv:1904.01720, 2019
1512019
Pixcolor: Pixel recursive colorization
S Guadarrama, R Dahl, D Bieber, M Norouzi, J Shlens, K Murphy
arXiv preprint arXiv:1705.07208, 2017
1232017
Language model cascades
D Dohan, W Xu, A Lewkowycz, J Austin, D Bieber, RG Lopes, Y Wu, ...
arXiv preprint arXiv:2207.10342, 2022
652022
BUSTLE: bottom-up program synthesis through learning-guided exploration
A Odena, K Shi, D Bieber, R Singh, C Sutton, H Dai
arXiv preprint arXiv:2007.14381, 2020
472020
Learning to execute programs with instruction pointer attention graph neural networks
D Bieber, C Sutton, H Larochelle, D Tarlow
Advances in Neural Information Processing Systems 33, 8626-8637, 2020
442020
Tf-coder: Program synthesis for tensor manipulations
K Shi, D Bieber, R Singh
ACM Transactions on Programming Languages and Systems (TOPLAS) 44 (2), 1-36, 2022
392022
Can large language models reason about program invariants?
K Pei, D Bieber, K Shi, C Sutton, P Yin
International Conference on Machine Learning, 27496-27520, 2023
322023
Show your work: Scratchpads for intermediate computation with language models, 2021
M Nye, AJ Andreassen, G Gur-Ari, H Michalewski, J Austin, D Bieber, ...
URL https://arxiv. org/abs/2112.00114, 2021
322021
Learning semantic representations to verify hardware designs
S Vasudevan, WJ Jiang, D Bieber, R Singh, CR Ho, C Sutton
Advances in Neural Information Processing Systems 34, 23491-23504, 2021
262021
Incremental sampling without replacement for sequence models
K Shi, D Bieber, C Sutton
International Conference on Machine Learning, 8785-8795, 2020
202020
Neural networks for modeling source code edits
R Zhao, D Bieber, K Swersky, D Tarlow
arXiv preprint arXiv:1904.02818, 2019
122019
Static prediction of runtime errors by learning to execute programs with external resource descriptions
D Bieber, R Goel, D Zheng, H Larochelle, D Tarlow
arXiv preprint arXiv:2203.03771, 2022
102022
Transforming grayscale images into color images using deep neural networks
SG Cotado, J Shlens, D Bieber, M Norouzi, KP Murphy, RL Dahl
US Patent 11,087,504, 2021
92021
Systems and methods for synthesizing code from input and output examples
K Shi, R Singh, DJ Bieber
US Patent 11,256,485, 2022
42022
A library for representing python programs as graphs for machine learning
D Bieber, K Shi, P Maniatis, C Sutton, V Hellendoorn, D Johnson, ...
arXiv preprint arXiv:2208.07461, 2022
32022
Can Large Language Models Reason About Program Invariants
C Sutton, D Bieber, K Shi, K Pei, P Yin
Proceedings of the International Conference on Machine Learning, 2023
22023
Systems and methods for synthesizing code from input and output examples
K Shi, R Singh, DJ Bieber
US Patent 11,875,139, 2024
2024
Prompting Machine-Learned Models Using Chains of Thought
JW Wei, D Zhou, DE Schuurmans, QV Le, MP Bosma, EHH Chi, ...
US Patent App. 17/881,746, 2023
2023
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