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)

On the Challenges of Physical Implementations of RBMs. - Vincent Dumoulin; Ian J. Goodfellow; Aaron C. Courville; Yoshua Bengio (AAAI, 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)

A guide to convolution arithmetic for deep learning. - Vincent Dumoulin; Francesco Visin (CoRR, 2016)

Discriminative Regularization for Generative Models. - Alex Lamb; Vincent Dumoulin; Aaron C. Courville (CoRR, 2016)

Exploring the structure of a real-time, arbitrary neural artistic stylization network. - Golnaz Ghiasi; Honglak Lee; Manjunath Kudlur; Vincent Dumoulin; Jonathon Shlens (BMVC, 2017)

Adversarially Learned Inference. - Vincent Dumoulin; Ishmael Belghazi; Ben Poole; Alex Lamb; Martín Arjovsky; Olivier Mastropietro; Aaron C. Courville (ICLR (Poster), 2017)

A Learned Representation For Artistic Style. - Vincent Dumoulin; Jonathon Shlens; Manjunath Kudlur (ICLR (Poster), 2017)

Improved Training of Wasserstein GANs. - Ishaan Gulrajani; Faruk Ahmed; Martín Arjovsky; Vincent Dumoulin; Aaron C. Courville (NIPS, 2017)

Learning Visual Reasoning Without Strong Priors. - Ethan Perez; Harm de Vries; Florian Strub; Vincent Dumoulin; Aaron C. Courville (CoRR, 2017)

FiLM: Visual Reasoning with a General Conditioning Layer. - Ethan Perez; Florian Strub; Harm de Vries; Vincent Dumoulin; Aaron C. Courville (AAAI, 2018)

Cross-Modulation Networks for Few-Shot Learning. - Hugo Prol; Vincent Dumoulin; Luis Herranz (CoRR, 2018)

Generative Adversarial Networks: An Overview. - Antonia Creswell; Tom White; Vincent Dumoulin; Kai Arulkumaran; Biswa Sengupta; Anil A. Bharath (IEEE Signal Process. Mag., 2018)

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)

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 (ICLR, 2020)

Domain Conditional Predictors for Domain Adaptation. - João Monteiro; Xavier Gibert Serra; Jianqiao Feng; Vincent Dumoulin; Dar-Shyang Lee (Preregister@NeurIPS, 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 001; Iain Dunning; Shibl Mourad; et al. (Artif. Intell., 2020)

An Effective Anti-Aliasing Approach for Residual Networks. - Cristina Nader Vasconcelos; Hugo Larochelle; Vincent Dumoulin; Nicolas Le Roux; Ross Goroshin (CoRR, 2020)

Impact of Aliasing on Generalization in Deep Convolutional Networks. - Cristina Nader Vasconcelos; Hugo Larochelle; Vincent Dumoulin; Rob Romijnders; Nicolas Le Roux; Ross Goroshin (ICCV, 2021)

Learning a Universal Template for Few-shot Dataset Generalization. - Eleni Triantafillou; Hugo Larochelle; Richard S. Zemel; Vincent Dumoulin (ICML, 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 (NeurIPS Datasets and Benchmarks, 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)

Proper Reuse of Image Classification Features Improves Object Detection. - Cristina Nader Vasconcelos; Vighnesh Birodkar; Vincent Dumoulin (CVPR, 2022)

APUF Faults: Impact, Testing, and Diagnosis. - Yeqi Wei; Tim Fox; Vincent Dumoulin; Wenjing Rao; Natasha Devroye (DATE, 2022)

Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning. - Utku Evci; Vincent Dumoulin; Hugo Larochelle; Michael C. Mozer (ICML, 2022)

Compositional Steering of Music Transformers 66-80. - Halley Young; Vincent Dumoulin; Pablo S. Castro; Jesse H. Engel; Cheng-Zhi Anna Huang (IUI Workshops, 2022)

Active learning for fast and slow modeling attacks on Arbiter PUFs. - Vincent Dumoulin; Wenjing Rao; Natasha Devroye (DSD, 2023)

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)

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)

Data Selection for Transfer Unlearning. - Nazanin Mohammadi Sepahvand; Vincent Dumoulin; Eleni Triantafillou; Gintare Karolina Dziugaite (CoRR, 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 001; Lisheng Sun-Hosoya; Sergio Escalera; et al. (CoRR, 2024)

A density estimation perspective on learning from pairwise human preferences. - Vincent Dumoulin; Daniel D. Johnson 001; Pablo Samuel Castro; Hugo Larochelle; Yann N. Dauphin (Trans. Mach. Learn. Res., 2024)

On the Response Entropy of APUFs. - Vincent Dumoulin; Wenjing Rao; Natasha Devroye (J. Hardw. Syst. Secur., 2024)

Capturing Individual Human Preferences with Reward Features. - André Barreto 001; Vincent Dumoulin; Yiran Mao; Nicolas Perez Nieves; Bobak Shahriari; Yann N. Dauphin; Doina Precup; Hugo Larochelle (CoRR, 2025)

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