Disentangling the Latent Space of (Variational) Autoencoders for NLP

Author:

Brunner Gino,Wang Yuyi,Wattenhofer Roger,Weigelt Michael

Publisher

Springer International Publishing

Reference9 articles.

1. Bengio, Y., Courville, A.C., Vincent, P.: Representation learning: a review and new perspectives. IEEE Trans. Pattern Anal. Mach. Intell. 35(8), 1798–1828 (2013). https://doi.org/10.1109/TPAMI.2013.50

2. Burgess, C.P., Higgins, I., Pal, A., Matthey, L., Watters, N., Desjardins, G., Lerchner, A.: Understanding disentangling in $$\beta $$β-VAE. arXiv preprint arXiv:180403599 (2018)

3. Higgins, I., Matthey, L., Pal, A., Burgess, C., Glorot, X., Botvinick, M., Mohamed, S., Lerchner, A.: $$\beta $$β-VAE: Learning basic visual concepts with a constrained variational framework (2016)

4. Kingma, D.P., Welling, M.: Auto-encoding variational bayes. CoRR abs/1312.6114. http://arxiv.org/abs/1312.6114 (2013)

5. Koehn, P.: Europarl: A Parallel Corpus for Statistical Machine Translation (2005)

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