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Committee Date Time Place Paper Title / Authors Abstract Paper #
SP, IPSJ-SLP, EA, SIP [detail] 2023-03-01
14:45
Okinawa
(Primary: On-site, Secondary: Online)
Personality Recognition on Dyadic Interactions with Representation Learning
Nathania Nah (Tokyo Tech), Takafumi Koshinaka (YCU), Koichi Shinoda (Tokyo Tech) EA2022-117 SIP2022-161 SP2022-81
Personality computing explores methods of automatically measuring human traits to create a better understanding of the h... [more] EA2022-117 SIP2022-161 SP2022-81
pp.241-246
PRMU 2022-09-15
10:45
Kanagawa
(Primary: On-site, Secondary: Online)
Effect validation of adversarial auxiliary classifier for video disentanglement
Takeshi Haga, Hiroshi Kera, Kazuhiko Kawamoto (Chiba Univ) PRMU2022-21
The Disentanglement of sequential data such as video requires inductive biases to separate static latent variables from ... [more] PRMU2022-21
pp.67-71
IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] 2022-02-21
16:45
Online Online A Note on Disentanglement Using Deep Generative Model Based on Variational Autoencoder -- Introduction of Regularization Losses Based on Metrics of Disentangled Representation --
Nao Nakagawa, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
In this paper, we study disentangled representation learning using a deep generative model based on Variational Autoenco... [more]
NLP, NC
(Joint)
2020-01-24
10:10
Okinawa Miyakojima Marine Terminal Optimal Transport based Autoencoder for class and style Disentanglement
Florian Tambon, Tetsuo Furukawa (Kyutech) NC2019-62
The Sinkhorn autoencoder is a novel generative model using optimal transport to model the aggregated posterior from samp... [more] NC2019-62
pp.17-22
 Results 1 - 4 of 4  /   
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