Publications and Preprints
- Teshima, T.*, Ishikawa, I.*, Tojo, K., Oono, K., Ikeda, M., and Sugiyama, M.,
Coupling-based invertible neural networks are universal diffeomorphism approximators.
- Fujisawa, M., Teshima, T., and Sato, I.,
γ-ABC: Outlier-robust approximate bayesian computation based on robust divergence estimator.
- Kato, M. and Teshima, T.,
Non-negative Bregman divergence minimization for deep direct density ratio estimation.
- Kato, M., Teshima, T., and Honda, J.,
Learning from positive and unlabeled data with a selection bias.
- Teshima, T., Xu, M., Sato, I., and Sugiyama, M.,
Clipped matrix completion: a remedy for ceiling effects.
[paper] [supplementary] [code] [slides]