| Dimensionality reduction by learning an invariant mapping R Hadsell, S Chopra, Y LeCun 2006 IEEE Computer Society Conference on Computer Vision and Pattern …, 2006 | 4775 | 2006 |
| Learning a similarity metric discriminatively, with application to face verification S Chopra, R Hadsell, Y LeCun 2005 IEEE Computer Society Conference on Computer Vision and Pattern …, 2005 | 4462 | 2005 |
| A neural attention model for abstractive sentence summarization AM Rush, S Chopra, J Weston arXiv preprint arXiv:1509.00685, 2015 | 3067 | 2015 |
| Memory networks J Weston, S Chopra, A Bordes arXiv preprint arXiv:1410.3916, 2014 | 2067 | 2014 |
| Efficient learning of sparse representations with an energy-based model MA Ranzato, C Poultney, S Chopra, Y Cun Advances in neural information processing systems 19, 2006 | 1773 | 2006 |
| Sequence level training with recurrent neural networks MA Ranzato, S Chopra, M Auli, W Zaremba arXiv preprint arXiv:1511.06732, 2015 | 1570 | 2015 |
| A tutorial on energy-based learning Y LeCun, S Chopra, R Hadsell, M Ranzato, F Huang Predicting structured data 1 (0), 2006 | 1208 | 2006 |
| Towards ai-complete question answering: A set of prerequisite toy tasks J Weston, A Bordes, S Chopra, AM Rush, B Van Merriënboer, A Joulin, ... arXiv preprint arXiv:1502.05698, 2015 | 1117 | 2015 |
| Abstractive sentence summarization with attentive recurrent neural networks S Chopra, M Auli, AM Rush Proceedings of the 2016 conference of the North American chapter of the …, 2016 | 1027 | 2016 |
| Question answering with subgraph embeddings A Bordes, S Chopra, J Weston arXiv preprint arXiv:1406.3676, 2014 | 886 | 2014 |
| Large-scale simple question answering with memory networks A Bordes, N Usunier, S Chopra, J Weston arXiv preprint arXiv:1506.02075, 2015 | 728 | 2015 |
| The goldilocks principle: Reading children's books with explicit memory representations F Hill, A Bordes, S Chopra, J Weston arXiv preprint arXiv:1511.02301, 2015 | 642 | 2015 |
| 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 | 474 | 2014 |
| Deep neural network improves fracture detection by clinicians R Lindsey, A Daluiski, S Chopra, A Lachapelle, M Mozer, S Sicular, ... Proceedings of the National Academy of Sciences 115 (45), 11591-11596, 2018 | 402 | 2018 |
| Learning longer memory in recurrent neural networks T Mikolov, A Joulin, S Chopra, M Mathieu, MA Ranzato arXiv preprint arXiv:1412.7753, 2014 | 299 | 2014 |
| Learning through dialogue interactions by asking questions J Li, AH Miller, S Chopra, MA Ranzato, J Weston arXiv preprint arXiv:1612.04936, 2016 | 296 | 2016 |
| Starspace: Embed all the things! L Wu, A Fisch, S Chopra, K Adams, A Bordes, J Weston Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 281 | 2018 |
| Dlid: Deep learning for domain adaptation by interpolating between domains S Chopra, S Balakrishnan, R Gopalan ICML workshop on challenges in representation learning 2 (6), 2013 | 238 | 2013 |
| 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 | 208 | 2015 |
| # tagspace: Semantic embeddings from hashtags J Weston, S Chopra, K Adams Proceedings of the 2014 conference on empirical methods in natural language …, 2014 | 196 | 2014 |
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