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pro vyhledávání: '"Probst, Malte"'
Autor:
Probst, Malte, Rothlauf, Franz
Estimation of Distribution Algorithms (EDAs) require flexible probability models that can be efficiently learned and sampled. Deep Boltzmann Machines (DBMs) are generative neural networks with these desired properties. We integrate a DBM into an EDA
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7bebe100e4228e11dc4cc1e79aa37361
Autor:
Probst, Malte
Estimation of Distribution Algorithms (EDAs) require flexible probability models that can be efficiently learned and sampled. Generative Adversarial Networks (GAN) are generative neural networks which can be trained to implicitly model the probabilit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::771e33f48584877f6beac85ad1446635