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)

Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets. - Pascal Vincent; Alexandre de Brébisson; Xavier Bouthillier (NIPS, 2015)

Dropout as data augmentation. - Kishore Reddy Konda; Xavier Bouthillier; Roland Memisevic; Pascal Vincent (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)

Exact gradient updates in time independent of output size for the spherical loss family. - Pascal Vincent; Alexandre de Brébisson; Xavier Bouthillier (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)

An Evaluation of Fisher Approximations Beyond Kronecker Factorization. - César Laurent; Thomas George; Xavier Bouthillier; Nicolas Ballas; Pascal Vincent (ICLR (Workshop), 2018)

Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis. - Thomas George; César Laurent; Xavier Bouthillier; Nicolas Ballas; Pascal Vincent (NeurIPS, 2018)

Unreproducible Research is Reproducible. - Xavier Bouthillier; César Laurent; Pascal Vincent (ICML, 2019)

Accounting for Variance in Machine Learning Benchmarks. - Xavier Bouthillier; Pierre Delaunay; Mirko Bronzi; Assya Trofimov; Brennan Nichyporuk; Justin Szeto; Nazanin Mohammadi Sepahvand; Edward Raff; Kanika Madan; Vikram Voleti; Samira Ebrahimi Kahou; Vincent Michalski; et al. (MLSys, 2021)

Accounting for Variance in Machine Learning Benchmarks. - Xavier Bouthillier; Pierre Delaunay; Mirko Bronzi; Assya Trofimov; Brennan Nichyporuk; Justin Szeto; Naz Sepah; Edward Raff; Kanika Madan; Vikram Voleti; Samira Ebrahimi Kahou; Vincent Michalski; et al. (CoRR, 2021)

LMEMs for post-hoc analysis of HPO Benchmarking. - Anton Geburek; Neeratyoy Mallik; Danny Stoll; Xavier Bouthillier; Frank Hutter (CoRR, 2024)

Introducing Milabench: Benchmarking Accelerators for AI. - Pierre Delaunay; Xavier Bouthillier; Olivier Breuleux; Satya Ortiz-Gagné; Olexa Bilaniuk; Fabrice Normandin; Arnaud Bergeron; Bruno Carrez; Guillaume Alain; Soline Blanc; Frédéric Osterrath; Joseph Viviano; et al. (CoRR, 2024)