125 citations · 309 across the 10 of their papers we have counts for
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stat.ML2016★ 49 cited
Generative Adversarial Nets from a Density Ratio Estimation Perspective
Masatoshi Uehara, Issei Sato, Masahiro Suzuki +2
Generative adversarial networks (GANs) are successful deep generative models. GANs are based on a two-player minimax game. However, the objective function derived in the original m…
stat.ML2016★ 125 cited
Joint Multimodal Learning with Deep Generative Models
Masahiro Suzuki, Kotaro Nakayama, Yutaka Matsuo
We investigate deep generative models that can exchange multiple modalities bi-directionally, e.g., generating images from corresponding texts and vice versa. Recently, some studie…