David Bieber

According to our database, David Bieber authored at least 15 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Can Large Language Models Reason about Program Invariants?

Kexin Pei, David Bieber, Kensen Shi, Charles Sutton, Pengcheng Yin

Proceedings of the International Conference on Machine Learning, 2023

Static Prediction of Runtime Errors by Learning to Execute Programs with External Resource Descriptions.

David Bieber, Rishab Goel, Daniel Zheng, Hugo Larochelle, Daniel Tarlow

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

TF-Coder: Program Synthesis for Tensor Manipulations.

Kensen Shi, David Bieber, Rishabh Singh

ACM Trans. Program. Lang. Syst., 2022

A Library for Representing Python Programs as Graphs for Machine Learning.

David Bieber, Kensen Shi, Petros Maniatis, Charles Sutton, Vincent J. Hellendoorn, Daniel D. Johnson, Daniel Tarlow

CoRR, 2022

Language Model Cascades.

David Dohan, Winnie Xu, Aitor Lewkowycz, Jacob Austin, David Bieber, Raphael Gontijo Lopes, Yuhuai Wu, Henryk Michalewski, Rif A. Saurous, Jascha Sohl-Dickstein, Kevin Murphy, Charles Sutton

CoRR, 2022

2021

Show Your Work: Scratchpads for Intermediate Computation with Language Models.

Maxwell I. Nye, Anders Johan Andreassen, Guy Gur-Ari, Henryk Michalewski, Jacob Austin, David Bieber, David Dohan, Aitor Lewkowycz, Maarten Bosma, David Luan, Charles Sutton, Augustus Odena

CoRR, 2021

Learning Semantic Representations to Verify Hardware Designs.

Shobha Vasudevan, Wenjie Jiang, David Bieber, Rishabh Singh, Hamid Shojaei, Richard Ho, Charles Sutton

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

BUSTLE: Bottom-Up Program Synthesis Through Learning-Guided Exploration.

Augustus Odena, Kensen Shi, David Bieber, Rishabh Singh, Charles Sutton, Hanjun Dai

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

BUSTLE: Bottom-up program-Synthesis Through Learning-guided Exploration.

Augustus Odena, Kensen Shi, David Bieber, Rishabh Singh, Charles Sutton

CoRR, 2020

Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks.

David Bieber, Charles Sutton, Hugo Larochelle, Daniel Tarlow

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Incremental Sampling Without Replacement for Sequence Models.

Kensen Shi, David Bieber, Charles Sutton

Proceedings of the 37th International Conference on Machine Learning, 2020

Global Relational Models of Source Code.

Vincent J. Hellendoorn, Charles Sutton, Rishabh Singh, Petros Maniatis, David Bieber

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Neural Networks for Modeling Source Code Edits.

Rui Zhao, David Bieber, Kevin Swersky, Daniel Tarlow

CoRR, 2019

Neural Program Repair by Jointly Learning to Localize and Repair.

Marko Vasic, Aditya Kanade, Petros Maniatis, David Bieber, Rishabh Singh

Proceedings of the 7th International Conference on Learning Representations, 2019

2017

PixColor: Pixel Recursive Colorization.

Sergio Guadarrama, Ryan Dahl, David Bieber, Jonathon Shlens, Mohammad Norouzi, Kevin Murphy

Proceedings of the British Machine Vision Conference 2017, 2017