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A Paper Accepted for KDD 2022

Our paper proposing a new conditional VAE (CVAE) that acquires task-invariant latent variables across different tasks has been accepted to KDD2022.
Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Sekitoshi Kanai, Masanori Yamada, Yuuki Yamanaka, Hisashi Kashima.
Learning Optimal Priors for Task-Invariant Representations in Variational Autoencoders.
In Proceedings of the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2022.