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NONPARAMETRIC DEEP CLUSTERING
3260 papers • 126 benchmarks • 313 datasets
Deep Nonparametric clustering are methods which utilize deep clustering when the number of clusters is not known apriorly and needs to be inferred.
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Most implemented papers
DIVA: A Dirichlet Process Mixtures Based Incremental Deep Clustering Algorithm via Variational Auto-Encoder
Hang Su, Alois Knoll, Zhenshan Bing, Y. Meng, Yuqi Yun, Xiaojie Su, Kai Huang•Mon May 22 2023
A nonparametric deep clustering framework that employs an infinite mixture of Gaussians as a prior, which outperforms state-of-the-art baselines, exhibits superior performance in classifying complex data with dynamically changing features, particularly in the case of incremental features.
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