Deep generative clustering methods based on disentangled representations and augmented data

Author:

Xu Kunxiong,Fan WentaoORCID,Liu Xin

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Reference64 articles.

1. Cai J, Wang S, Guo W (2021) Unsupervised embedded feature learning for deep clustering with stacked sparse auto-encoder. Expert Syst Appl 186(115):729

2. Cao L, Asadi S, Zhu W, Schmidli C, Sjöberg M (2020) Simple, scalable, and stable variational deep clustering. In: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp 108–124

3. Chen RT, Li X, Grosse RB, Duvenaud DK (2018) Isolating sources of disentanglement in variational autoencoders. vol 31

4. Chen X, Duan Y, Houthooft R, Schulman J, Sutskever I, Abbeel P (2016) Infogan: Interpretable representation learning by information maximizing generative adversarial nets. In: Advances in neural information processing systems, vol 29

5. Dai Q, Zhao C, Zhao S (2022) Variational bayesian student’st mixture model with closed-form missing value imputation for robust process monitoring of low-quality data. IEEE Trans Cybern pp 1–14

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