Sainbayar Sukhbaatar
Sainbayar Sukhbaatar
PhD student, Dept. of Computer Science, New York University
Verified email at - Homepage
Cited by
Cited by
End-To-End Memory Networks
S Sukhbaatar, A Szlam, J Weston, R Fergus
Learning multiagent communication with backpropagation
S Sukhbaatar, A Szlam, R Fergus
Advances in Neural Information Processing Systems, 2244-2252, 2016
Training Convolutional Networks with Noisy Labels
S Sukhbaatar, J Bruna, M Paluri, L Bourdev, R Fergus
Accepted as a workshop contribution at ICLR 2015, 2014
Simple baseline for visual question answering
B Zhou, Y Tian, S Sukhbaatar, A Szlam, R Fergus
arXiv preprint arXiv:1512.02167, 2015
Intrinsic motivation and automatic curricula via asymmetric self-play
S Sukhbaatar, Z Lin, I Kostrikov, G Synnaeve, A Szlam, R Fergus
arXiv preprint arXiv:1703.05407, 2017
Mazebase: A sandbox for learning from games
S Sukhbaatar, A Szlam, G Synnaeve, S Chintala, R Fergus
arXiv preprint arXiv:1511.07401, 2015
Adaptive attention span in transformers
S Sukhbaatar, E Grave, P Bojanowski, A Joulin
arXiv preprint arXiv:1905.07799, 2019
Learning when to communicate at scale in multiagent cooperative and competitive tasks
A Singh, T Jain, S Sukhbaatar
arXiv preprint arXiv:1812.09755, 2018
Composable planning with attributes
A Zhang, S Sukhbaatar, A Lerer, A Szlam, R Fergus
International Conference on Machine Learning, 5842-5851, 2018
Robust Generation of Dynamical Patterns in Human Motion by a Deep Belief Nets
S Sukhbaatar, T Makino, K Aihara, T Chikayama
Asian Conference on Machine Learning, 231--246, 2011
Augmenting self-attention with persistent memory
S Sukhbaatar, E Grave, G Lample, H Jegou, A Joulin
arXiv preprint arXiv:1907.01470, 2019
End-to-end memory networks
JE Weston, AD Szlam, RD Fergus, S Sukhbaatar
US Patent 10,664,744, 2020
Learning goal embeddings via self-play for hierarchical reinforcement learning
S Sukhbaatar, E Denton, A Szlam, R Fergus
arXiv preprint arXiv:1811.09083, 2018
Auto-pooling: Learning to improve invariance of image features from image sequences
S Sukhbaatar, T Makino, K Aihara
arXiv preprint arXiv:1301.3323, 2013
Accessing Higher-level Representations in Sequential Transformers with Feedback Memory
A Fan, T Lavril, E Grave, A Joulin, S Sukhbaatar
arXiv preprint arXiv:2002.09402, 2020
Learning from noisy labels with deep neural networks,” arXiv
S Sukhbaatar, R Fergus
Learning to Visually Navigate in Photorealistic Environments Without any Supervision
L Mezghani, S Sukhbaatar, A Szlam, A Joulin, P Bojanowski
arXiv preprint arXiv:2004.04954, 2020
Training hybrid language models by marginalizing over segmentations
É Grave, S Sukhbaatar, P Bojanowski, A Joulin
Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019
Unsupervised training sets for content classification
RD Fergus, L Bourdev, B Paluri, S Sukhbaatar
US Patent 10,360,498, 2019
Planning with Arithmetic and Geometric Attributes
D Folqué, S Sukhbaatar, A Szlam, J Bruna
arXiv preprint arXiv:1809.02031, 2018
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