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Daniel Tarlow

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Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs

Feb 13, 2024
Daniel D. Johnson, Daniel Tarlow, David Duvenaud, Chris J. Maddison

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R-U-SURE? Uncertainty-Aware Code Suggestions By Maximizing Utility Across Random User Intents

Mar 01, 2023
Daniel D. Johnson, Daniel Tarlow, Christian Walder

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A Library for Representing Python Programs as Graphs for Machine Learning

Aug 15, 2022
David Bieber, Kensen Shi, Petros Maniatis, Charles Sutton, Vincent Hellendoorn, Daniel Johnson, Daniel Tarlow

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Learning to Improve Code Efficiency

Aug 09, 2022
Binghong Chen, Daniel Tarlow, Kevin Swersky, Martin Maas, Pablo Heiber, Ashish Naik, Milad Hashemi, Parthasarathy Ranganathan

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Repository-Level Prompt Generation for Large Language Models of Code

Jun 26, 2022
Disha Shrivastava, Hugo Larochelle, Daniel Tarlow

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

Mar 07, 2022
David Bieber, Rishab Goel, Daniel Zheng, Hugo Larochelle, Daniel Tarlow

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Learning Generalized Gumbel-max Causal Mechanisms

Nov 11, 2021
Guy Lorberbom, Daniel D. Johnson, Chris J. Maddison, Daniel Tarlow, Tamir Hazan

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Beyond In-Place Corruption: Insertion and Deletion In Denoising Probabilistic Models

Jul 16, 2021
Daniel D. Johnson, Jacob Austin, Rianne van den Berg, Daniel Tarlow

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Structured Denoising Diffusion Models in Discrete State-Spaces

Jul 13, 2021
Jacob Austin, Daniel D. Johnson, Jonathan Ho, Daniel Tarlow, Rianne van den Berg

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Learning to Combine Per-Example Solutions for Neural Program Synthesis

Jun 14, 2021
Disha Shrivastava, Hugo Larochelle, Daniel Tarlow

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