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 (EMNLP, 2014)

On the Properties of Neural Machine Translation: Encoder-Decoder Approaches. - Kyunghyun Cho; Bart van Merrienboer; Dzmitry Bahdanau; Yoshua Bengio (SSST@EMNLP, 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 (SSST@EMNLP, 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)

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)

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; et al. (CoRR, 2016)

Multiscale sequence modeling with a learned dictionary. - Bart van Merriënboer; Amartya Sanyal; Hugo Larochelle; Yoshua Bengio (CoRR, 2017)

Tangent: Automatic Differentiation Using Source Code Transformation in Python. - Bart van Merriënboer; Alexander B. Wiltschko; Dan Moldovan (CoRR, 2017)

Automatic differentiation in ML: Where we are and where we should be going. - Bart van Merrienboer; Olivier Breuleux; Arnaud Bergeron; Pascal Lamblin (NeurIPS, 2018)

Tangent: Automatic differentiation using source-code transformation for dynamically typed array programming. - Bart van Merrienboer; Dan Moldovan; Alexander B. Wiltschko (NeurIPS, 2018)

Information matrices and generalization. - Valentin Thomas; Fabian Pedregosa; Bart van Merriënboer; Pierre-Antoine Manzagol; Yoshua Bengio; Nicolas Le Roux (CoRR, 2019)

Fast Training of Sparse Graph Neural Networks on Dense Hardware. - Matej Balog; Bart van Merriënboer; Subhodeep Moitra; Yujia Li; Daniel Tarlow (CoRR, 2019)

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 (AISTATS, 2020)

GradMax: Growing Neural Networks using Gradient Information. - Utku Evci; Bart van Merrienboer; Thomas Unterthiner; Fabian Pedregosa; Max Vladymyrov (ICLR, 2022)

In Search for a Generalizable Method for Source Free Domain Adaptation. - Malik Boudiaf; Tom Denton; Bart van Merrienboer; Vincent Dumoulin; Eleni Triantafillou (ICML, 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)

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., 2023)

Leveraging tropical reef, bird and unrelated sounds for superior transfer learning in marine bioacoustics. - Ben Williams; Bart van Merriënboer; Vincent Dumoulin; Jenny Hamer; Eleni Triantafillou; Abram B. Fleishman; Matthew McKown; Jill E. Munger; Aaron N. Rice; Ashlee Lillis; Clemency E. White; Catherine A. D. Hobbs; et al. (CoRR, 2024)

Perch 2.0: The Bittern Lesson for Bioacoustics. - Bart van Merriënboer; Vincent Dumoulin; Jenny Hamer; Lauren Harrell; Andrea Burns; Tom Denton (CoRR, 2025)