Teshima, Takeshi

8 publications

JMLR 2023 Universal Approximation Property of Invertible Neural Networks Isao Ishikawa, Takeshi Teshima, Koichi Tojo, Kenta Oono, Masahiro Ikeda, Masashi Sugiyama

AISTATS 2021 Γ-ABC: Outlier-Robust Approximate Bayesian Computation Based on a Robust Divergence Estimator Masahiro Fujisawa, Takeshi Teshima, Issei Sato, Masashi Sugiyama

UAI 2021 Incorporating Causal Graphical Prior Knowledge into Predictive Modeling via Simple Data Augmentation Takeshi Teshima, Masashi Sugiyama

ICML 2021 Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation Masahiro Kato, Takeshi Teshima

NeurIPS 2020 Coupling-Based Invertible Neural Networks Are Universal Diffeomorphism Approximators Takeshi Teshima, Isao Ishikawa, Koichi Tojo, Kenta Oono, Masahiro Ikeda, Masashi Sugiyama

ICML 2020 Few-Shot Domain Adaptation by Causal Mechanism Transfer Takeshi Teshima, Issei Sato, Masashi Sugiyama

AAAI 2019 Clipped Matrix Completion: A Remedy for Ceiling Effects Takeshi Teshima, Miao Xu, Issei Sato, Masashi Sugiyama

ICLR 2019 Learning from Positive and Unlabeled Data with a Selection Bias Masahiro Kato, Takeshi Teshima, Junya Honda