Greedy Layer-Wise Training of Deep Networks. - Yoshua Bengio; Pascal Lamblin; Dan Popovici; Hugo Larochelle (NIPS, 2006)

Learning the 2-D Topology of Images. - Nicolas Le Roux; Yoshua Bengio; Pascal Lamblin; Marc Joliveau; Balázs Kégl (NIPS, 2007)

Exploring Strategies for Training Deep Neural Networks. - Hugo Larochelle; Yoshua Bengio; Jérôme Louradour; Pascal Lamblin (J. Mach. Learn. Res., 2009)

Theano: A CPU and GPU Math Compiler in Python. - James Bergstra; Olivier Breuleux; Frédéric Bastien; Pascal Lamblin; Razvan Pascanu; Guillaume Desjardins; Joseph P. Turian; David Warde-Farley; Yoshua Bengio (SciPy, 2010)

Theano: new features and speed improvements - Frédéric Bastien; Pascal Lamblin; Razvan Pascanu; James Bergstra; Ian J. Goodfellow; Arnaud Bergeron; Nicolas Bouchard; David Warde-Farley; Yoshua Bengio (CoRR, 2012)

Combining modality specific deep neural networks for emotion recognition in video. - Samira Ebrahimi Kahou; Christopher J. Pal; Xavier Bouthillier; Pierre Froumenty; Çaglar Gülçehre; Roland Memisevic; Pascal Vincent; Aaron C. Courville; Yoshua Bengio; Raul Chandias Ferrari; Mehdi Mirza; Sébastien Jean; et al. (ICMI, 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)

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)

EmoNets: Multimodal deep learning approaches for emotion recognition in video. - Samira Ebrahimi Kahou; Xavier Bouthillier; Pascal Lamblin; Çaglar Gülçehre; Vincent Michalski; Kishore Konda; Sébastien Jean; Pierre Froumenty; Yann N. Dauphin; Nicolas Boulanger-Lewandowski; Raul Chandias Ferrari; Mehdi Mirza; et al. (J. Multimodal User Interfaces, 2016)

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

PLUR: A Unifying, Graph-Based View of Program Learning, Understanding, and Repair. - Zimin Chen; Vincent J. Hellendoorn; Pascal Lamblin; Petros Maniatis; Pierre-Antoine Manzagol; Daniel Tarlow; Subhodeep Moitra (NeurIPS, 2021)

AI-Assisted Assessment of Coding Practices in Modern Code Review. - Manushree Vijayvergiya; Malgorzata Salawa; Ivan Budiselic; Dan Zheng; Pascal Lamblin; Marko Ivankovic; Juanjo Carin; Mateusz Lewko; Jovan Andonov; Goran Petrovic; Daniel Tarlow; Petros Maniatis; et al. (AIware, 2024)

Resolving Code Review Comments with Machine Learning. - Alexander Frömmgen; Jacob Austin; Peter Choy; Nimesh Ghelani; Lera Kharatyan; Gabriela Surita; Elena Khrapko; Pascal Lamblin; Pierre-Antoine Manzagol; Marcus Revaj; Maxim Tabachnyk; Daniel Tarlow; et al. (ICSE-SEIP, 2024)

Unlearning in- vs. out-of-distribution data in LLMs under gradient-based method. - Teodora Baluta; Pascal Lamblin; Daniel Tarlow; Fabian Pedregosa; Gintare Karolina Dziugaite (CoRR, 2024)