Bart van MerriŽnboer
Bart van MerriŽnboer
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Title
Cited by
Cited by
Year
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
K Cho, B van Merrienboer, C Gulcehre, F Bougares, H Schwenk, ...
arXiv preprint arXiv:1406.1078, 2014
161272014
On the Properties of Neural Machine Translation: Encoder-Decoder Approaches
K Cho, B van MerriŽnboer, D Bahdanau, Y Bengio
arXiv preprint arXiv:1409.1259, 2014
42572014
Towards AI-complete question answering: a set of prerequisite toy tasks
J Weston, A Bordes, S Chopra, T Mikolov, B van MerriŽnboer
arXiv preprint arXiv:1502.05698, 2015
9362015
Theano: A Python framework for fast computation of mathematical expressions
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
arXiv preprint arXiv:1605.02688, 2016
8212016
Blocks and Fuel: Frameworks for deep learning
B van MerriŽnboer, D Bahdanau, V Dumoulin, D Serdyuk, ...
arXiv preprint arXiv:1506.00619, 2015
1842015
Overcoming the Curse of Sentence Length for Neural Machine Translation using Automatic Segmentation
J Pouget-Abadie, D Bahdanau, B van MerriŽnboer, K Cho, Y Bengio
arXiv preprint arXiv:1409.1257, 2014
652014
Automatic differentiation in ML: Where we are and where we should be going
B van MerriŽnboer, O Breuleux, A Bergeron, P Lamblin
Advances in neural information processing systems, 8757-8767, 2018
392018
Tangent: Automatic differentiation using source-code transformation for dynamically typed array programming
B van MerriŽnboer, D Moldovan, A Wiltschko
Advances in Neural Information Processing Systems, 6256-6265, 2018
262018
Information matrices and generalization
V Thomas, F Pedregosa, B van MerriŽnboer, PA Mangazol, Y Bengio, ...
arXiv preprint arXiv:1906.07774, 2019
102019
Tangent: Automatic Differentiation Using Source Code Transformation in Python
B van MerriŽnboer, AB Wiltschko, D Moldovan
arXiv preprint arXiv:1711.02712, 2017
7*2017
Automatic Differentiation in Myia
O Breuleux, B van MerriŽnboer
72017
Multiscale sequence modeling with a learned dictionary
B van MerriŽnboer, A Sanyal, H Larochelle, Y Bengio
arXiv preprint arXiv:1707.00762, 2017
72017
Halting time is predictable for large models: A universality property and average-case analysis
C Paquette, B van MerriŽnboer, E Paquette, F Pedregosa
arXiv preprint arXiv:2006.04299, 2020
62020
Fast Training of Sparse Graph Neural Networks on Dense Hardware
M Balog, B van MerriŽnboer, S Moitra, Y Li, D Tarlow
arXiv preprint arXiv:1906.11786, 2019
42019
Sequence-to-sequence learning for machine translation and automatic differentiation for machine learning software tools
B van MerriŽnboer
12019
Optimizing sparse graph neural networks for dense hardware
DS Tarlow, M Balog, B Van Merrienboer, Y Li, S Moitra
US Patent App. 16/883,209, 2020
2020
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