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Daniel Tarlow
Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks

Oct 23, 2020
David Bieber, Charles Sutton, Hugo Larochelle, Daniel Tarlow

* Accepted at NeurIPS 2020 
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Software Engineering Event Modeling using Relative Time in Temporal Knowledge Graphs

Jul 13, 2020
Kian Ahrabian, Daniel Tarlow, Hehuimin Cheng, Jin L. C. Guo

* 11 pages, 1 figure. 37th International Conference on Machine Learning (ICML 2020) - Workshop on Graph Representation Learning and Beyond 
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Learning Graph Structure With A Finite-State Automaton Layer

Jul 09, 2020
Daniel D. Johnson, Hugo Larochelle, Daniel Tarlow

* Submitted to NeurIPS 2020 
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Gradient Estimation with Stochastic Softmax Tricks

Jun 15, 2020
Max B. Paulus, Dami Choi, Daniel Tarlow, Andreas Krause, Chris J. Maddison


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On-the-Fly Adaptation of Source Code Models using Meta-Learning

Mar 26, 2020
Disha Shrivastava, Hugo Larochelle, Daniel Tarlow


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Learning to Fix Build Errors with Graph2Diff Neural Networks

Nov 04, 2019
Daniel Tarlow, Subhodeep Moitra, Andrew Rice, Zimin Chen, Pierre-Antoine Manzagol, Charles Sutton, Edward Aftandilian

* Submitted for review on Aug 23, 2019 
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Fast Training of Sparse Graph Neural Networks on Dense Hardware

Jun 27, 2019
Matej Balog, Bart van Merriënboer, Subhodeep Moitra, Yujia Li, Daniel Tarlow


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Learning Execution through Neural Code Fusion

Jun 17, 2019
Zhan Shi, Kevin Swersky, Daniel Tarlow, Parthasarathy Ranganathan, Milad Hashemi

* 14 pages,7 figures 
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Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces

Jun 14, 2019
Guy Lorberbom, Chris J. Maddison, Nicolas Heess, Tamir Hazan, Daniel Tarlow


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Neural Networks for Modeling Source Code Edits

Apr 04, 2019
Rui Zhao, David Bieber, Kevin Swersky, Daniel Tarlow

* Deanonymized version of ICLR 2019 submission 
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Graph Partition Neural Networks for Semi-Supervised Classification

Mar 16, 2018
Renjie Liao, Marc Brockschmidt, Daniel Tarlow, Alexander L. Gaunt, Raquel Urtasun, Richard Zemel


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Gated Graph Sequence Neural Networks

Sep 22, 2017
Yujia Li, Daniel Tarlow, Marc Brockschmidt, Richard Zemel

* Published as a conference paper in ICLR 2016. Fixed a typo 
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AMPNet: Asynchronous Model-Parallel Training for Dynamic Neural Networks

Jun 22, 2017
Alexander L. Gaunt, Matthew A. Johnson, Maik Riechert, Daniel Tarlow, Ryota Tomioka, Dimitrios Vytiniotis, Sam Webster

* 17 pages, 13 figures 
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DeepCoder: Learning to Write Programs

Mar 08, 2017
Matej Balog, Alexander L. Gaunt, Marc Brockschmidt, Sebastian Nowozin, Daniel Tarlow

* Submitted to ICLR 2017 
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Differentiable Programs with Neural Libraries

Mar 02, 2017
Alexander L. Gaunt, Marc Brockschmidt, Nate Kushman, Daniel Tarlow


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Differentiable Functional Program Interpreters

Mar 02, 2017
John K. Feser, Marc Brockschmidt, Alexander L. Gaunt, Daniel Tarlow


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Summary - TerpreT: A Probabilistic Programming Language for Program Induction

Dec 02, 2016
Alexander L. Gaunt, Marc Brockschmidt, Rishabh Singh, Nate Kushman, Pushmeet Kohli, Jonathan Taylor, Daniel Tarlow

* 7 pages, 2 figures, 4 tables in 1st Workshop on Neural Abstract Machines & Program Induction (NAMPI), @NIPS 2016 
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TerpreT: A Probabilistic Programming Language for Program Induction

Aug 15, 2016
Alexander L. Gaunt, Marc Brockschmidt, Rishabh Singh, Nate Kushman, Pushmeet Kohli, Jonathan Taylor, Daniel Tarlow

* 50 pages, 20 figures, 4 tables 
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Consensus Message Passing for Layered Graphical Models

Jan 26, 2015
Varun Jampani, S. M. Ali Eslami, Daniel Tarlow, Pushmeet Kohli, John Winn

* Appearing in Proceedings of the 18th International Conference on Artificial Intelligence and Statistics (AISTATS) 2015 
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A* Sampling

Jan 26, 2015
Chris J. Maddison, Daniel Tarlow, Tom Minka

* V2: - reworded the last paragraph of Section 2 to clarify that the argmax is a sample from the normalized measure. - fixed notation in Algorithm 1. - fixed a typo in paragraph 2 of Section 5 
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Candidate Constrained CRFs for Loss-Aware Structured Prediction

Dec 10, 2014
Faruk Ahmed, Daniel Tarlow, Dhruv Batra

* 20 pages including Supplement 
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Structured Generative Models of Natural Source Code

Jun 20, 2014
Chris J. Maddison, Daniel Tarlow


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Detecting Parameter Symmetries in Probabilistic Models

Dec 19, 2013
Robert Nishihara, Thomas Minka, Daniel Tarlow

* 24 pages, 8 figures 
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Tighter Linear Program Relaxations for High Order Graphical Models

Sep 26, 2013
Elad Mezuman, Daniel Tarlow, Amir Globerson, Yair Weiss

* Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI2013) 
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Fast Exact Inference for Recursive Cardinality Models

Oct 16, 2012
Daniel Tarlow, Kevin Swersky, Richard S. Zemel, Ryan Prescott Adams, Brendan J. Frey

* Appears in Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI2012) 
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Flexible Priors for Exemplar-based Clustering

Jun 13, 2012
Daniel Tarlow, Richard S. Zemel, Brendan J. Frey

* Appears in Proceedings of the Twenty-Fourth Conference on Uncertainty in Artificial Intelligence (UAI2008) 
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Interpreting Graph Cuts as a Max-Product Algorithm

May 05, 2011
Daniel Tarlow, Inmar E. Givoni, Richard S. Zemel, Brendan J. Frey


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