Disentangling Factors of Variation for Facial Expression Recognition. - Salah Rifai; Yoshua Bengio; Aaron C. Courville; Pascal Vincent; Mehdi Mirza (ECCV (6), 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)

Maxout Networks. - Ian J. Goodfellow; David Warde-Farley; Mehdi Mirza; Aaron C. Courville; Yoshua Bengio (ICML (3), 2013)

Challenges in Representation Learning: A Report on Three Machine Learning Contests. - Ian J. Goodfellow; Dumitru Erhan; Pierre Luc Carrier; Aaron C. Courville; Mehdi Mirza; Benjamin Hamner; William Cukierski; Yichuan Tang; David Thaler; Dong-Hyun Lee; Yingbo Zhou; Chetan Ramaiah; et al. (ICONIP (3), 2013)

Multi-Prediction Deep Boltzmann Machines. - Ian J. Goodfellow; Mehdi Mirza; Aaron C. Courville; Yoshua Bengio (NIPS, 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)

Generative Adversarial Nets. - Ian J. Goodfellow; Jean Pouget-Abadie; Mehdi Mirza; Bing Xu; David Warde-Farley; Sherjil Ozair; Aaron C. Courville; Yoshua Bengio (NIPS, 2014)

An Empirical Investigation of Catastrophic Forgeting in Gradient-Based Neural Networks. - Ian J. Goodfellow; Mehdi Mirza; Xia Da; Aaron C. Courville; Yoshua Bengio (ICLR (Poster), 2014)

Conditional Generative Adversarial Nets. - Mehdi Mirza; Simon Osindero (CoRR, 2014)

Challenges in representation learning: A report on three machine learning contests. - Ian J. Goodfellow; Dumitru Erhan; Pierre Luc Carrier; Aaron C. Courville; Mehdi Mirza; Benjamin Hamner; William Cukierski; Yichuan Tang; David Thaler; Dong-Hyun Lee; Yingbo Zhou; Chetan Ramaiah; et al. (Neural Networks, 2015)

Asynchronous Methods for Deep Reinforcement Learning. - Volodymyr Mnih; Adrià Puigdomènech Badia; Mehdi Mirza; Alex Graves; Timothy P. Lillicrap; Tim Harley; David Silver; Koray Kavukcuoglu (ICML, 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; 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)

Generalizable Features From Unsupervised Learning. - Mehdi Mirza; Aaron C. Courville; Yoshua Bengio (ICLR (Workshop), 2017)

Unsupervised Predictive Memory in a Goal-Directed Agent. - Greg Wayne; Chia-Chun Hung; David Amos; Mehdi Mirza; Arun Ahuja; Agnieszka Grabska-Barwinska; Jack W. Rae; Piotr Mirowski; Joel Z. Leibo; Adam Santoro; Mevlana Gemici; Malcolm Reynolds; et al. (CoRR, 2018)

Probing Physics Knowledge Using Tools from Developmental Psychology. - Luis Piloto; Ari Weinstein; Dhruva TB; Arun Ahuja; Mehdi Mirza; Greg Wayne; David Amos; Chia-Chun Hung; Matthew M. Botvinick (CoRR, 2018)

Optimizing Agent Behavior over Long Time Scales by Transporting Value. - Chia-Chun Hung; Timothy P. Lillicrap; Josh Abramson; Yan Wu 010; Mehdi Mirza; Federico Carnevale; Arun Ahuja; Greg Wayne (CoRR, 2018)

An Investigation of Model-Free Planning. - Arthur Guez; Mehdi Mirza; Karol Gregor; Rishabh Kabra; Sébastien Racanière; Theophane Weber; David Raposo; Adam Santoro; Laurent Orseau; Tom Eccles; Greg Wayne; David Silver; et al. (ICML, 2019)

Generative adversarial networks. - Ian J. Goodfellow; Jean Pouget-Abadie; Mehdi Mirza; Bing Xu; David Warde-Farley; Sherjil Ozair; Aaron C. Courville; Yoshua Bengio (Commun. ACM, 2020)

Physically Embedded Planning Problems: New Challenges for Reinforcement Learning. - Mehdi Mirza; Andrew Jaegle; Jonathan J. Hunt; Arthur Guez; Saran Tunyasuvunakool; Alistair Muldal; Théophane Weber; Péter Karkus; Sébastien Racanière; Lars Buesing; Timothy P. Lillicrap; Nicolas Heess (CoRR, 2020)

Beyond Tabula-Rasa: a Modular Reinforcement Learning Approach for Physically Embedded 3D Sokoban. - Péter Karkus; Mehdi Mirza; Arthur Guez; Andrew Jaegle; Timothy P. Lillicrap; Lars Buesing; Nicolas Heess; Theophane Weber (CoRR, 2020)

Evaluating Model-Based Planning and Planner Amortization for Continuous Control. - Arunkumar Byravan; Leonard Hasenclever; Piotr Trochim; Mehdi Mirza; Alessandro Davide Ialongo; Yuval Tassa; Jost Tobias Springenberg; Abbas Abdolmaleki; Nicolas Heess; Josh Merel; Martin A. Riedmiller (ICLR, 2022)

Retrieval-Augmented Reinforcement Learning. - Anirudh Goyal; Abram L. Friesen; Andrea Banino; Theophane Weber; Nan Rosemary Ke; Adrià Puigdomènech Badia; Arthur Guez; Mehdi Mirza; Peter Conway Humphreys; Ksenia Konyushkova; Michal Valko; Simon Osindero; et al. (ICML, 2022)

Retrieval-Augmented Reinforcement Learning. - Anirudh Goyal; Abram L. Friesen; Andrea Banino; Theophane Weber; Nan Rosemary Ke; Adrià Puigdomènech Badia; Arthur Guez; Mehdi Mirza; Ksenia Konyushkova; Michal Valko; Simon Osindero; Timothy P. Lillicrap; et al. (CoRR, 2022)