Bart van Merrienboer

According to our database, Bart van Merrienboer authored at least 17 papers between 2014 and 2023.

Collaborative distances:

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

2023

Halting Time is Predictable for Large Models: A Universality Property and Average-Case Analysis.

Courtney Paquette, Bart van Merriënboer, Elliot Paquette, Fabian Pedregosa

Found. Comput. Math., April, 2023

BIRB: A Generalization Benchmark for Information Retrieval in Bioacoustics.

Jenny Hamer, Eleni Triantafillou, Bart van Merriënboer, Stefan Kahl, Holger Klinck, Tom Denton, Vincent Dumoulin

CoRR, 2023

In Search for a Generalizable Method for Source Free Domain Adaptation.

Malik Boudiaf, Tom Denton, Bart van Merrienboer, Vincent Dumoulin, Eleni Triantafillou

Proceedings of the International Conference on Machine Learning, 2023

2022

GradMax: Growing Neural Networks using Gradient Information.

Utku Evci, Bart van Merrienboer, Thomas Unterthiner, Fabian Pedregosa, Max Vladymyrov

Proceedings of the Tenth International Conference on Learning Representations, 2022

2020

On the interplay between noise and curvature and its effect on optimization and generalization.

Valentin Thomas, Fabian Pedregosa, Bart van Merriënboer, Pierre-Antoine Manzagol, Yoshua Bengio, Nicolas Le Roux

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Fast Training of Sparse Graph Neural Networks on Dense Hardware.

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

CoRR, 2019

Information matrices and generalization.

Valentin Thomas, Fabian Pedregosa, Bart van Merriënboer, Pierre-Antoine Manzagol, Yoshua Bengio, Nicolas Le Roux

CoRR, 2019

2018

Tangent: Automatic differentiation using source-code transformation for dynamically typed array programming.

Bart van Merrienboer, Dan Moldovan, Alexander B. Wiltschko

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Automatic differentiation in ML: Where we are and where we should be going.

Bart van Merrienboer, Olivier Breuleux, Arnaud Bergeron, Pascal Lamblin

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Tangent: Automatic Differentiation Using Source Code Transformation in Python.

Bart van Merriënboer, Alexander B. Wiltschko, Dan Moldovan

CoRR, 2017

Multiscale sequence modeling with a learned dictionary.

Bart van Merriënboer, Amartya Sanyal, Hugo Larochelle, Yoshua Bengio

CoRR, 2017

2016

Theano: A Python framework for fast computation of mathematical expressions.

Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermüller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang

CoRR, 2016

2015

Blocks and Fuel: Frameworks for deep learning.

Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin, Dmitriy Serdyuk, David Warde-Farley, Jan Chorowski, Yoshua Bengio

CoRR, 2015

2014

Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.

Kyunghyun Cho, Bart van Merrienboer, Çaglar Gülçehre, Fethi Bougares, Holger Schwenk, Yoshua Bengio

CoRR, 2014

Overcoming the Curse of Sentence Length for Neural Machine Translation using Automatic Segmentation.

Jean Pouget-Abadie, Dzmitry Bahdanau, Bart van Merrienboer, Kyunghyun Cho, Yoshua Bengio

Proceedings of SSST@EMNLP 2014, 2014

On the Properties of Neural Machine Translation: Encoder-Decoder Approaches.

Kyunghyun Cho, Bart van Merrienboer, Dzmitry Bahdanau, Yoshua Bengio

Proceedings of SSST@EMNLP 2014, 2014

Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.

Kyunghyun Cho, Bart van Merrienboer, Çaglar Gülçehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, Yoshua Bengio

Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, 2014