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Results: 34
Number of items: 34
  • Open Access
    Bastings, J., Aziz, W., & Titov, I. (2019). Interpretable Neural Predictions with Differentiable Binary Variables. In A. Korhonen, D. Traum, & L. Màrquez (Eds.), The 57th Annual Meeting of the Association for Computational Linguistics: ACL 2019 : proceedings of the conference : July 28-August 2, 2019, Florence, Italy (pp. 2963-2977). The Association for Computational Linguistics. https://doi.org/10.18653/v1/P19-1284
  • Open Access
    Calixto, I., Rios, M., & Aziz, W. (2019). Latent Variable Model for Multi-modal Translation. In A. Korhonen, D. Traum, & L. Màrquez (Eds.), The 57th Annual Meeting of the Association for Computational Linguistics: ACL 2019 : proceedings of the conference : July 28-August 2, 2019, Florence, Italy (pp. 6392–6405). The Association for Computational Linguistics. https://doi.org/10.18653/v1/P19-1642
  • Open Access
    Eikema, B., & Aziz, W. (2019). Auto-Encoding Variational Neural Machine Translation. In I. Augenstein, S. Gella, S. Ruder, K. Kann, J. Welbl, A. Conneau, X. Ren, & M. Rei (Eds.), The 4th Workshop on Representation Learning for NLP (RepL4NLP-2019): ACL 2019 : proceedings of the workshop : August 2, 2019, Florence, Italy (pp. 124–141). The Association for Computational Linguistics. https://doi.org/10.18653/v1/W19-4315
  • Open Access
    De Cao, N., Aziz, W., & Titov, I. (2019). Question answering by reasoning across documents with graph convolutional networks. In J. Burstein, C. Doran, & T. Solorio (Eds.), The 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: NAACL HLT 2019 : proceedings of the conference : June 2-June 7, 2019 (Vol. 1, pp. 2306-2317). The Association for Computational Linguistics. https://doi.org/10.18653/v1/N19-1240
  • Open Access
    Rios, M., Aziz, W., & Sima'an, K. (2018). Deep Generative Model for Joint Alignment and Word Representation. In M. Walker, H. Ji, & A. Stent (Eds.), NAACL-HLT 2018 : The 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: proceedings of the conference : June 1-June 6, 2018, New Orleans, Louisiana (Vol. 1, pp. 1011-1023). The Association for Computational Linguistics. https://doi.org/10.18653/v1/N18-1092
  • Open Access
    Schulz, P., Aziz, W., & Cohn, T. (2018). A Stochastic Decoder for Neural Machine Translation. In I. Gurevych, & Y. Miyao (Eds.), ACL 2018 : The 56th Annual Meeting of the Association for Computational Linguistics: proceedings of the conference : July 15-20, 2018, Melbourne, Australia (Vol. 1, pp. 1243-1252). The Association for Computational Linguistics. https://doi.org/10.18653/v1/P18-1115
  • Open Access
    Daiber, J. (2018). Typologically robust statistical machine translation: Understanding and exploiting differences and similarities between languages in machine translation. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Bastings, J., Titov, I., Aziz, W., Marcheggiani, D., & Sima'an, K. (2017). Graph Convolutional Encoders for Syntax-aware Neural Machine Translation. In M. Palmer, R. Hwa, & S. Riedel (Eds.), The Conference on Empirical Methods in Natural Language Processing: proceedings of the conference : EMNLP 2017 : September 9-11, 2017, Copenhagen, Denmark (pp. 1957-1967). Association for Computational Linguistics. https://doi.org/10.18653/v1/D17-1209
  • Open Access
    Stanojević , M. (2017). Permutation forests for modeling word order in machine translation. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Daiber, J., Stanojević, M., Aziz, W., & Sima'an, K. (2016). Examining the Relationship between Preordering and Word Order Freedom in Machine Translation. In Proceedings of the First Conference on Machine Translation: Berlin, Germany, August 11-12, 2016 (Vol. 1, pp. 118-130). Association for Computational Linguistics. https://doi.org/10.18653/v1/W16-2213
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