David Bieber
David Bieber
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Cited by
Cited by
Global relational models of source code
VJ Hellendoorn, C Sutton, R Singh, P Maniatis, D Bieber
International conference on learning representations, 2019
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
Pixcolor: Pixel recursive colorization
S Guadarrama, R Dahl, D Bieber, M Norouzi, J Shlens, K Murphy
arXiv preprint arXiv:1705.07208, 2017
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
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
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
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
Neural networks for modeling source code edits
R Zhao, D Bieber, K Swersky, D Tarlow
arXiv preprint arXiv:1904.02818, 2019
Incremental sampling without replacement for sequence models
K Shi, D Bieber, C Sutton
International Conference on Machine Learning, 8785-8795, 2020
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
Language model cascades
D Dohan, W Xu, A Lewkowycz, J Austin, D Bieber, RG Lopes, Y Wu, ...
arXiv preprint arXiv:2207.10342, 2022
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
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
Systems and Methods for Synthesizing Code from Input and Output Examples
K Shi, R Singh, DJ Bieber
US Patent App. 17/676,601, 2022
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
Systems and methods for synthesizing code from input and output examples
K Shi, R Singh, DJ Bieber
US Patent 11,256,485, 2022
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