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Found 4 papers, 1 papers with code
A variational autoencoder-based nonnegative matrix factorisation model for deep dictionary learning
Construction of dictionaries using nonnegative matrix factorisation (NMF) has extensive applications in signal processing and machine learning.
Scalable Deep Generative Relational Model with High-Order Node Dependence
In this work, we propose a probabilistic framework for relational data modelling and latent structure exploring.
Scalable Deep Generative Relational Models with High-Order Node Dependence
We propose a probabilistic framework for modelling and exploring the latent structure of relational data.
Comment on "Clustering by fast search and find of density peaks"
For any data set to be clustered, the most reasonable value of d_c can be objectively calculated from the data set by using our proposed method.
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