Arthur Szlam
Arthur Szlam
Adresă de e-mail confirmată pe google.com
Citat de
Citat de
Spectral networks and locally connected networks on graphs
J Bruna, W Zaremba, A Szlam, Y LeCun
arXiv preprint arXiv:1312.6203, 2013
Geometric deep learning: going beyond euclidean data
MM Bronstein, J Bruna, Y LeCun, A Szlam, P Vandergheynst
IEEE Signal Processing Magazine 34 (4), 18-42, 2017
End-to-end memory networks
S Sukhbaatar, A Szlam, J Weston, R Fergus
Advances in neural information processing systems 28, 2015
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks
E Denton, S Chintala, A Szlam, R Fergus
Advances in neural information processing systems 28, 2015
Personalizing dialogue agents: I have a dog, do you have pets too?
S Zhang, E Dinan, J Urbanek, A Szlam, D Kiela, J Weston
arXiv preprint arXiv:1801.07243, 2018
Learning multiagent communication with backpropagation
S Sukhbaatar, A Szlam, R Fergus
Advances in Neural Information Processing Systems, 2244-2252, 2016
Video (language) modeling: a baseline for generative models of natural videos
MA Ranzato, A Szlam, J Bruna, M Mathieu, R Collobert, S Chopra
arXiv preprint arXiv:1412.6604, 2014
A randomized algorithm for principal component analysis
V Rokhlin, A Szlam, M Tygert
SIAM Journal on Matrix Analysis and Applications 31 (3), 1100-1124, 2010
Optimizing the latent space of generative networks
P Bojanowski, A Joulin, D Lopez-Paz, A Szlam
arXiv preprint arXiv:1707.05776, 2017
Incremental gradient on the grassmannian for online foreground and background separation in subsampled video
J He, L Balzano, A Szlam
2012 IEEE Conference on Computer Vision and Pattern Recognition, 1568-1575, 2012
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
Simple baseline for visual question answering
B Zhou, Y Tian, S Sukhbaatar, A Szlam, R Fergus
arXiv preprint arXiv:1512.02167, 2015
The second conversational intelligence challenge (convai2)
E Dinan, V Logacheva, V Malykh, A Miller, K Shuster, J Urbanek, D Kiela, ...
The NeurIPS'18 Competition: From Machine Learning to Intelligent …, 2020
Tracking the world state with recurrent entity networks
M Henaff, J Weston, A Szlam, A Bordes, Y LeCun
arXiv preprint arXiv:1612.03969, 2016
Dialogue natural language inference
S Welleck, J Weston, A Szlam, K Cho
arXiv preprint arXiv:1811.00671, 2018
Hybrid linear modeling via local best-fit flats
T Zhang, A Szlam, Y Wang, G Lerman
International journal of computer vision 100, 217-240, 2012
Blenderbot 3: a deployed conversational agent that continually learns to responsibly engage
K Shuster, J Xu, M Komeili, D Ju, EM Smith, S Roller, M Ung, M Chen, ...
arXiv preprint arXiv:2208.03188, 2022
Modeling others using oneself in multi-agent reinforcement learning
R Raileanu, E Denton, A Szlam, R Fergus
International conference on machine learning, 4257-4266, 2018
Evaluating prerequisite qualities for learning end-to-end dialog systems
J Dodge, A Gane, X Zhang, A Bordes, S Chopra, A Miller, A Szlam, ...
arXiv preprint arXiv:1511.06931, 2015
Beyond goldfish memory: Long-term open-domain conversation
J Xu, A Szlam, J Weston
arXiv preprint arXiv:2107.07567, 2021
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