| Neural machine translation by jointly learning to align and translate D Bahdanau, K Cho, Y Bengio arXiv preprint arXiv:1409.0473, 2014 | 10262 | 2014 |
| Learning phrase representations using RNN encoder-decoder for statistical machine translation K Cho, B Van Merriënboer, C Gulcehre, D Bahdanau, F Bougares, ... arXiv preprint arXiv:1406.1078, 2014 | 7747 | 2014 |
| On the properties of neural machine translation: Encoder-decoder approaches K Cho, B Van Merriënboer, D Bahdanau, Y Bengio arXiv preprint arXiv:1409.1259, 2014 | 2225 | 2014 |
| Attention-based models for speech recognition JK Chorowski, D Bahdanau, D Serdyuk, K Cho, Y Bengio Advances in neural information processing systems, 577-585, 2015 | 1011 | 2015 |
| End-to-end attention-based large vocabulary speech recognition D Bahdanau, J Chorowski, D Serdyuk, P Brakel, Y Bengio 2016 IEEE international conference on acoustics, speech and signal …, 2016 | 607 | 2016 |
| Theano: A Python framework for fast computation of mathematical expressions R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ... arXiv preprint arXiv:1605.02688, 2016 | 573 | 2016 |
| An actor-critic algorithm for sequence prediction D Bahdanau, P Brakel, K Xu, A Goyal, R Lowe, J Pineau, A Courville, ... arXiv preprint arXiv:1607.07086, 2016 | 283 | 2016 |
| End-to-end continuous speech recognition using attention-based recurrent nn: First results J Chorowski, D Bahdanau, K Cho, Y Bengio arXiv preprint arXiv:1412.1602, 2014 | 242 | 2014 |
| Neural machine translation by jointly learning to align and translate (2014) D Bahdanau, K Cho, Y Bengio arXiv preprint arXiv:1409.0473 9, 2014 | 197 | 2014 |
| Blocks and fuel: Frameworks for deep learning B Van Merriënboer, D Bahdanau, V Dumoulin, D Serdyuk, ... arXiv preprint arXiv:1506.00619, 2015 | 152 | 2015 |
| Neural machine translation by jointly learning to align and translate. arXiv 2014 D Bahdanau, K Cho, Y Bengio arXiv preprint arXiv:1409.0473, 2014 | 66 | 2014 |
| Sequence tutor: Conservative fine-tuning of sequence generation models with kl-control N Jaques, S Gu, D Bahdanau, JM Hernández-Lobato, RE Turner, D Eck Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017 | 52 | 2017 |
| On the properties of neural machine translation: Encoder-decoder approaches. arXiv 2014 K Cho, B Van Merriënboer, D Bahdanau, Y Bengio arXiv preprint arXiv:1409.1259, 0 | 50 | |
| Overcoming the curse of sentence length for neural machine translation using automatic segmentation J Pouget-Abadie, D Bahdanau, B Van Merrienboer, K Cho, Y Bengio arXiv preprint arXiv:1409.1257, 2014 | 35 | 2014 |
| Learning to compute word embeddings on the fly D Bahdanau, T Bosc, S Jastrzębski, E Grefenstette, P Vincent, Y Bengio arXiv preprint arXiv:1706.00286, 2017 | 30 | 2017 |
| Learning to understand goal specifications by modelling reward D Bahdanau, F Hill, J Leike, E Hughes, A Hosseini, P Kohli, ... arXiv preprint arXiv:1806.01946, 2018 | 28* | 2018 |
| BabyAI: First Steps Towards Grounded Language Learning With a Human In the Loop M Chevalier-Boisvert, D Bahdanau, S Lahlou, L Willems, C Saharia, ... arXiv preprint arXiv:1810.08272, 2018 | 26* | 2018 |
| Task loss estimation for sequence prediction D Bahdanau, D Serdyuk, P Brakel, NR Ke, J Chorowski, A Courville, ... arXiv preprint arXiv:1511.06456, 2015 | 24 | 2015 |
| Systematic generalization: what is required and can it be learned? D Bahdanau, S Murty, M Noukhovitch, TH Nguyen, H de Vries, A Courville arXiv preprint arXiv:1811.12889, 2018 | 9 | 2018 |
| Commonsense mining as knowledge base completion? A study on the impact of novelty S Jastrzębski, D Bahdanau, S Hosseini, M Noukhovitch, Y Bengio, ... arXiv preprint arXiv:1804.09259, 2018 | 6 | 2018 |
