Sherjil Ozair
Cited by
Cited by
Generative Adversarial Networks
I Goodfellow, J Pouget-Abadie, M Mirza, B Xu, D Warde-Farley, S Ozair, ...
Advances in neural information processing systems 27, 2014
Generative Adversarial Networks
I Goodfellow, J Pouget-Abadie, M Mirza, B Xu, D Warde-Farley, S Ozair, ...
Communications of the ACM 63 (11), 139-144, 2020
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
D Amodei, S Ananthanarayanan, R Anubhai, J Bai, E Battenberg, C Case, ...
International conference on machine learning, 173-182, 2016
Mutual Information Neural Estimation
MI Belghazi, A Baratin, S Rajeshwar, S Ozair, Y Bengio, A Courville, ...
International conference on machine learning, 531-540, 2018
On Variational Bounds of Mutual Information
B Poole, S Ozair, A Van Den Oord, A Alemi, G Tucker
International Conference on Machine Learning, 5171-5180, 2019
Unsupervised State Representation Learning in Atari
A Anand, E Racah, S Ozair, Y Bengio, MA Côté, RD Hjelm
Advances in neural information processing systems 32, 2019
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
Mastering the game of Stratego with model-free multiagent reinforcement learning
J Perolat, B De Vylder, D Hennes, E Tarassov, F Strub, V de Boer, ...
Science 378 (6623), 990-996, 2022
Maximum entropy generators for energy-based models
R Kumar, S Ozair, A Goyal, A Courville, Y Bengio
arXiv preprint arXiv:1901.08508, 2019
Wasserstein dependency measure for representation learning
S Ozair, C Lynch, Y Bengio, A Van den Oord, S Levine, P Sermanet
Advances in Neural Information Processing Systems 32, 2019
Efficient synthesis of probabilistic programs
AV Nori, S Ozair, SK Rajamani, D Vijaykeerthy
ACM SIGPLAN Notices 50 (6), 208-217, 2015
On variational lower bounds of mutual information
B Poole, S Ozair, A van den Oord, AA Alemi, G Tucker
NeurIPS Workshop on Bayesian Deep Learning, 2018
Planning in stochastic environments with a learned model
I Antonoglou, J Schrittwieser, S Ozair, TK Hubert, D Silver
International Conference on Learning Representations, 2021
Vector quantized models for planning
S Ozair, Y Li, A Razavi, I Antonoglou, A Van Den Oord, O Vinyals
international conference on machine learning, 8302-8313, 2021
Procedural generalization by planning with self-supervised world models
A Anand, J Walker, Y Li, E Vértes, J Schrittwieser, S Ozair, T Weber, ...
arXiv preprint arXiv:2111.01587, 2021
Deep directed generative autoencoders
S Ozair, Y Bengio
arXiv preprint arXiv:1410.0630, 2014
StarCraft II Unplugged: Large Scale Offline Reinforcement Learning
M Mathieu, S Ozair, S Srinivasan, C Gulcehre, S Zhang, R Jiang, ...
Deep RL Workshop NeurIPS 2021, 2021
On the equivalence between deep nade and generative stochastic networks
L Yao, S Ozair, K Cho, Y Bengio
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2014
Sketchtransfer: A new dataset for exploring detail-invariance and the abstractions learned by deep networks
A Lamb, S Ozair, V Verma, D Ha
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2020
Multimodal transitions for generative stochastic networks
S Ozair, L Yao, Y Bengio
arXiv preprint arXiv:1312.5578, 2013
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