SCGN: novel generative model using the convergence of latent space by training
Sign Up to like & getrecommendations! Published in 2020 at "Electronics Letters"
DOI: 10.1049/el.2020.1333
Abstract: Generative models such as variational autoencoders (VAEs) and generative adversarial networks (GANs) have been recently applied to various fields. However, the VAE and GAN models have blur and mode collapse problems, respectively. Here, the authors… read more here.
Keywords: convergence latent; generative model; novel generative; latent vectors ... See more keywords
Polytopic Matrix Factorization: Determinant Maximization Based Criterion and Identifiability
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2021.3112918
Abstract: We introduce Polytopic Matrix Factorization (PMF) as a novel data decomposition approach. In this new framework, we model input data as unknown linear transformations of some latent vectors drawn from a polytope. In this sense,… read more here.
Keywords: matrix; polytope; latent vectors; factorization ... See more keywords