| Neural machine translation by jointly learning to align and translate D Bahdanau, K Cho, Y Bengio arXiv preprint arXiv:1409.0473, 2014 | 30951 | 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 | 25943 | 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 | 7537 | 2014 |
| Attention-based models for speech recognition JK Chorowski, D Bahdanau, D Serdyuk, K Cho, Y Bengio Advances in neural information processing systems 28, 2015 | 2898 | 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 | 1368 | 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 e-prints, arXiv: 1605.02688, 2016 | 1071* | 2016 |
| Learning phrase representations using RNN encoder-decoder for statistical machine translation. arXiv 2014 K Cho, B Van Merriënboer, C Gulcehre, D Bahdanau, F Bougares, ... arXiv preprint arXiv:1406.1078, 2020 | 914 | 2020 |
| Neural machine translation by jointly learning to align and translate. arXiv 2014 D Bahdanau, K Cho, Y Bengio arXiv preprint arXiv:1409.0473, 2014 | 633 | 2014 |
| 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 | 632 | 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 | 554 | 2014 |
| 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 | 294* | 2018 |
| Blocks and fuel: Frameworks for deep learning B Van Merriënboer, D Bahdanau, V Dumoulin, D Serdyuk, ... arXiv preprint arXiv:1506.00619, 2015 | 202 | 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 | 176 | 2018 |
| 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 | 163* | 2018 |
| 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 International Conference on Machine Learning, 1645-1654, 2017 | 157 | 2017 |
| PICARD: Parsing incrementally for constrained auto-regressive decoding from language models T Scholak, N Schucher, D Bahdanau arXiv preprint arXiv:2109.05093, 2021 | 141 | 2021 |
| Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) K Cho, B van Merrienboer, C Gulcehre, D Bahdanau, F Bougares, ... Association for Computational Linguistics. https://doi. org/10.3115/v1/d14-1179, 2014 | 103 | 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 | 91 | 2017 |
| 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 | 91 | 2014 |
| Closure: Assessing systematic generalization of clevr models D Bahdanau, H de Vries, TJ O'Donnell, S Murty, P Beaudoin, Y Bengio, ... arXiv preprint arXiv:1912.05783, 2019 | 88* | 2019 |
