Danny Tarlow

Membre Industriel Principal
Danny Tarlow
Professeur adjoint, McGill University, Google
Danny Tarlow

Danny Tarlow est chercheur scientifique chez Google Brain. Il s’intéresse principalement aux méthodes d’apprentissage automatique pour comprendre et générer des programmes. Il est également professeur auxiliaire à l’École d’informatique de l’Université McGill. Titulaire d’un doctorat du groupe d’apprentissage automatique de l’Université de Toronto, il a passé quatre ans comme post-doctorant puis chercheur chez Microsoft Research, à Cambridge, avant de venir à Montréal.

Publications

2020-11

OPTIMIZING SPARSE GRAPH NEURAL NETWORKS FOR DENSE HARDWARE
Tarlow Daniel S, Balog Matej, Van Merrienboer Bart, Li Yujia and Moitra Subhodeep
(venue unknown)
(2020-11-26)
lens.org

2020-10

Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks.
David Bieber, Charles Sutton, Hugo Larochelle and Daniel Tarlow
arXiv: Learning
(2020-10-26)
arxiv.orgPDF

2020-07

Learning Graph Structure With A Finite-State Automaton Layer.
Daniel D. Johnson, Hugo Larochelle and Daniel Tarlow
arXiv: Learning
(2020-07-09)
dblp.uni-trier.dePDF
Software Engineering Event Modeling using Relative Time in Temporal Knowledge Graphs.
Kian Ahrabian, Daniel Tarlow, Hehuimin Cheng and Jin L. C. Guo
arXiv preprint arXiv:2007.01231
(2020-07-02)
dblp.uni-trier.dePDF

2020-06

Learning to Fix Build Errors with Graph2Diff Neural Networks
Daniel Tarlow, Subhodeep Moitra, Andrew Rice, Zimin Chen, Pierre-Antoine Manzagol, Charles Sutton and Edward Aftandilian
ICSE 2020
(2020-06-27)
dblp.uni-trier.dePDF
Gradient Estimation with Stochastic Softmax Tricks
Max B. Paulus, Dami Choi, Daniel Tarlow, Andreas Krause and Chris J. Maddison
NEURIPS 2020
(2020-06-15)
papers.nips.cc
Gradient Estimation with Stochastic Softmax Tricks
Max B. Paulus, Dami Choi, Daniel Tarlow, Andreas Krause and Chris J. Maddison
arXiv preprint arXiv:2006.08063
(2020-06-15)
dblp.uni-trier.dePDF

2020-04

LEARNING EXECUTION THROUGH NEURAL CODE FUSION
Zhan Shi, Kevin Swersky, Daniel Tarlow, Parthasarathy Ranganathan and Milad Hashemi

2020-03

On-the-Fly Adaptation of Source Code Models using Meta-Learning
Disha Shrivastava, Hugo Larochelle and Daniel Tarlow
arXiv preprint arXiv:2003.11768
(2020-03-26)
dblp.uni-trier.dePDF

2020-01

Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces
Guy Lorberbom, Chris J. Maddison, Nicolas Heess, Tamir Hazan and Daniel Tarlow
NEURIPS 2020
(2020-01-01)
papers.nips.cc
Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks
David Bieber, Charles Sutton, Hugo Larochelle and Daniel Tarlow
NEURIPS 2020
(2020-01-01)
papers.nips.cc
Learning Graph Structure With A Finite-State Automaton Layer
Daniel D. Johnson, Hugo Larochelle and Daniel Tarlow
NEURIPS 2020
(2020-01-01)
papers.nips.cc

2019-11

Learning to Fix Build Errors with Graph2Diff Neural Networks.
Daniel Tarlow, Subhodeep Moitra, Andrew Rice, Zimin Chen, Pierre-Antoine Manzagol, Charles Sutton and Edward Aftandilian
arXiv preprint arXiv:1911.01205
(2019-11-04)
dblp.uni-trier.dePDF

2019-09

Fast Training of Sparse Graph Neural Networks on Dense Hardware
Matej Balog, Bart van Merriënboer, Subhodeep Moitra, Yujia Li and Daniel Tarlow
arXiv preprint arXiv:1906.11786
(2019-09-25)
dblp.uni-trier.dePDF

2019-06

Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces.
Guy Lorberbom, Chris J. Maddison, Nicolas Heess, Tamir Hazan and Daniel Tarlow
arXiv preprint arXiv:1906.06062
(2019-06-14)
dblp.uni-trier.dePDF

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