Bart van Merriënboer

16 papers A 1Journal 15

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Perch 2.0 transfers 'whale' to underwater tasks. CoRR Andrea Burns, Lauren Harrell, Bart van Merriënboer, Vincent Dumoulin, Jenny Hamer, Tom Denton
2025	J	`jnl`	Perch 2.0: The Bittern Lesson for Bioacoustics. CoRR Bart van Merriënboer, Vincent Dumoulin, Jenny Hamer, Lauren Harrell, Andrea Burns, Tom Denton
2024	J	`jnl`	Leveraging tropical reef, bird and unrelated sounds for superior transfer learning in marine bioacoustics. CoRR 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, Tries B. Razak, Kate E. Jones, Tom Denton
2023	J	`jnl`	BIRB: A Generalization Benchmark for Information Retrieval in Bioacoustics. CoRR Jenny Hamer, Eleni Triantafillou, Bart van Merriënboer, Stefan Kahl, Holger Klinck, Tom Denton, Vincent Dumoulin
2023	J	`jnl`	Halting Time is Predictable for Large Models: A Universality Property and Average-Case Analysis. Found. Comput. Math. Courtney Paquette, Bart van Merriënboer, Elliot Paquette, Fabian Pedregosa
2023	J	`jnl`	In Search for a Generalizable Method for Source Free Domain Adaptation. CoRR Malik Boudiaf, Tom Denton, Bart van Merriënboer, Vincent Dumoulin, Eleni Triantafillou
2022	J	`jnl`	GradMax: Growing Neural Networks using Gradient Information. CoRR Utku Evci, Max Vladymyrov, Thomas Unterthiner, Bart van Merriënboer, Fabian Pedregosa
2020	A	`conf`	On the interplay between noise and curvature and its effect on optimization and generalization. AISTATS Valentin Thomas, Fabian Pedregosa, Bart van Merriënboer, Pierre-Antoine Manzagol, Yoshua Bengio, Nicolas Le Roux
2019	J	`jnl`	Fast Training of Sparse Graph Neural Networks on Dense Hardware. CoRR Matej Balog, Bart van Merriënboer, Subhodeep Moitra, Yujia Li, Daniel Tarlow
2019	J	`jnl`	Information matrices and generalization. CoRR Valentin Thomas, Fabian Pedregosa, Bart van Merriënboer, Pierre-Antoine Manzagol, Yoshua Bengio, Nicolas Le Roux
2018	J	`jnl`	Automatic differentiation in ML: Where we are and where we should be going. CoRR Bart van Merriënboer, Olivier Breuleux, Arnaud Bergeron, Pascal Lamblin
2018	J	`jnl`	Tangent: Automatic differentiation using source-code transformation for dynamically typed array programming. CoRR Bart van Merriënboer, Dan Moldovan, Alexander B. Wiltschko
2017	J	`jnl`	Multiscale sequence modeling with a learned dictionary. CoRR Bart van Merriënboer, Amartya Sanyal, Hugo Larochelle, Yoshua Bengio
2017	J	`jnl`	Tangent: Automatic Differentiation Using Source Code Transformation in Python. CoRR Bart van Merriënboer, Alexander B. Wiltschko, Dan Moldovan
2016	J	`jnl`	Theano: A Python framework for fast computation of mathematical expressions. CoRR 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
2015	J	`jnl`	Blocks and Fuel: Frameworks for deep learning. CoRR Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin, Dmitriy Serdyuk, David Warde-Farley, Jan Chorowski, Yoshua Bengio