Vincent Dumoulin

According to our database, Vincent Dumoulin authored at least 35 papers between 2013 and 2024.

Collaborative distances:

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

2024

On the Response Entropy of APUFs.

Vincent Dumoulin, Wenjing Rao, Natasha Devroye

J. Hardw. Syst. Secur., September, 2024

A density estimation perspective on learning from pairwise human preferences.

Vincent Dumoulin, Daniel D. Johnson, Pablo Samuel Castro, Hugo Larochelle, Yann N. Dauphin

Trans. Mach. Learn. Res., 2024

Are we making progress in unlearning? Findings from the first NeurIPS unlearning competition.

Eleni Triantafillou, Peter Kairouz, Fabian Pedregosa, Jamie Hayes, Meghdad Kurmanji, Kairan Zhao, Vincent Dumoulin, Júlio C. S. Jacques Júnior, Ioannis Mitliagkas, Jun Wan, Lisheng Sun-Hosoya, Sergio Escalera, Gintare Karolina Dziugaite, Peter Triantafillou, Isabelle Guyon

CoRR, 2024

Data Selection for Transfer Unlearning.

Nazanin Mohammadi Sepahvand, Vincent Dumoulin, Eleni Triantafillou, Gintare Karolina Dziugaite

CoRR, 2024

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, Tries B. Razak, Kate E. Jones, Tom Denton

CoRR, 2024

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

Active learning for fast and slow modeling attacks on Arbiter PUFs.

Vincent Dumoulin, Wenjing Rao, Natasha Devroye

Proceedings of the 26th Euromicro Conference on Digital System Design, 2023

2022

Compositional Steering of Music Transformers 66-80.

Halley Young, Vincent Dumoulin, Pablo S. Castro, Jesse H. Engel, Cheng-Zhi Anna Huang

Proceedings of the Joint Proceedings of the IUI 2022 Workshops: APEx-UI, 2022

Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning.

Utku Evci, Vincent Dumoulin, Hugo Larochelle, Michael C. Mozer

Proceedings of the International Conference on Machine Learning, 2022

APUF Faults: Impact, Testing, and Diagnosis.

Yeqi Wei, Tim Fox, Vincent Dumoulin, Wenjing Rao, Natasha Devroye

Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

Proper Reuse of Image Classification Features Improves Object Detection.

Cristina Nader Vasconcelos, Vighnesh Birodkar, Vincent Dumoulin

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark.

Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle

CoRR, 2021

A Unified Few-Shot Classification Benchmark to Compare Transfer and Meta Learning Approaches.

Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Learning a Universal Template for Few-shot Dataset Generalization.

Eleni Triantafillou, Hugo Larochelle, Richard S. Zemel, Vincent Dumoulin

Proceedings of the 38th International Conference on Machine Learning, 2021

Impact of Aliasing on Generalization in Deep Convolutional Networks.

Cristina Nader Vasconcelos, Hugo Larochelle, Vincent Dumoulin, Rob Romijnders, Nicolas Le Roux, Ross Goroshin

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

An Effective Anti-Aliasing Approach for Residual Networks.

Cristina Nader Vasconcelos, Hugo Larochelle, Vincent Dumoulin, Nicolas Le Roux, Ross Goroshin

CoRR, 2020

The Hanabi challenge: A new frontier for AI research.

Nolan Bard, Jakob N. Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, H. Francis Song, Emilio Parisotto, Vincent Dumoulin, Subhodeep Moitra, Edward Hughes, Iain Dunning, Shibl Mourad, Hugo Larochelle, Marc G. Bellemare, Michael Bowling

Artif. Intell., 2020

Domain Conditional Predictors for Domain Adaptation.

João Monteiro, Xavier Gibert Serra, Jianqiao Feng, Vincent Dumoulin, Dar-Shyang Lee

Proceedings of the NeurIPS 2020 Workshop on Pre-registration in Machine Learning, 2020

Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples.

Eleni Triantafillou, Tyler Zhu, Vincent Dumoulin, Pascal Lamblin, Utku Evci, Kelvin Xu, Ross Goroshin, Carles Gelada, Kevin Swersky, Pierre-Antoine Manzagol, Hugo Larochelle

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples.

Eleni Triantafillou, Tyler Zhu, Vincent Dumoulin, Pascal Lamblin, Kelvin Xu, Ross Goroshin, Carles Gelada, Kevin Swersky, Pierre-Antoine Manzagol, Hugo Larochelle

CoRR, 2019

2018

Generative Adversarial Networks: An Overview.

Antonia Creswell, Tom White, Vincent Dumoulin, Kai Arulkumaran, Biswa Sengupta, Anil A. Bharath

IEEE Signal Process. Mag., 2018

Cross-Modulation Networks for Few-Shot Learning.

Hugo Prol, Vincent Dumoulin, Luis Herranz

CoRR, 2018

FiLM: Visual Reasoning with a General Conditioning Layer.

Ethan Perez, Florian Strub, Harm de Vries, Vincent Dumoulin, Aaron C. Courville

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Learning Visual Reasoning Without Strong Priors.

Ethan Perez, Harm de Vries, Florian Strub, Vincent Dumoulin, Aaron C. Courville

CoRR, 2017

Improved Training of Wasserstein GANs.

Ishaan Gulrajani, Faruk Ahmed, Martín Arjovsky, Vincent Dumoulin, Aaron C. Courville

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A Learned Representation For Artistic Style.

Vincent Dumoulin, Jonathon Shlens, Manjunath Kudlur

Proceedings of the 5th International Conference on Learning Representations, 2017

Adversarially Learned Inference.

Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martín Arjovsky, Olivier Mastropietro, Aaron C. Courville

Proceedings of the 5th International Conference on Learning Representations, 2017

Exploring the structure of a real-time, arbitrary neural artistic stylization network.

Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin, Jonathon Shlens

Proceedings of the British Machine Vision Conference 2017, 2017

2016

Discriminative Regularization for Generative Models.

Alex Lamb, Vincent Dumoulin, Aaron C. Courville

CoRR, 2016

A guide to convolution arithmetic for deep learning.

Vincent Dumoulin, Francesco Visin

CoRR, 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

On the Challenges of Physical Implementations of RBMs.

Vincent Dumoulin, Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013

Pylearn2: a machine learning research library.

Ian J. Goodfellow, David Warde-Farley, Pascal Lamblin, Vincent Dumoulin, Mehdi Mirza, Razvan Pascanu, James Bergstra, Frédéric Bastien, Yoshua Bengio

CoRR, 2013