Takeshi Teshima

17 papers A* 4A 2Journal 10Unranked 1

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Universal Approximation Property of Invertible Neural Networks. J. Mach. Learn. Res. Isao Ishikawa, Takeshi Teshima, Koichi Tojo, Kenta Oono, Masahiro Ikeda, Masashi Sugiyama
2022	J	`jnl`	Universal approximation property of invertible neural networks. CoRR Isao Ishikawa, Takeshi Teshima, Koichi Tojo, Kenta Oono, Masahiro Ikeda, Masashi Sugiyama
2021	J	`jnl`	Incorporating Causal Graphical Prior Knowledge into Predictive Modeling via Simple Data Augmentation. CoRR Takeshi Teshima, Masashi Sugiyama
2021	A	`conf`	Incorporating causal graphical prior knowledge into predictive modeling via simple data augmentation. UAI Takeshi Teshima, Masashi Sugiyama
2021	A*	`conf`	Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation. ICML Masahiro Kato, Takeshi Teshima
2021	J	`jnl`	Rethinking Importance Weighting for Transfer Learning. CoRR Nan Lu, Tianyi Zhang, Tongtong Fang, Takeshi Teshima, Masashi Sugiyama
2021	A	`conf`	γ-ABC: Outlier-Robust Approximate Bayesian Computation Based on a Robust Divergence Estimator. AISTATS Masahiro Fujisawa, Takeshi Teshima, Issei Sato, Masashi Sugiyama
2020	A*	`conf`	Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators. NeurIPS Takeshi Teshima, Isao Ishikawa, Koichi Tojo, Kenta Oono, Masahiro Ikeda, Masashi Sugiyama
2020	J	`jnl`	Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators. CoRR Takeshi Teshima, Isao Ishikawa, Koichi Tojo, Kenta Oono, Masahiro Ikeda, Masashi Sugiyama
2020	A*	`conf`	Few-shot Domain Adaptation by Causal Mechanism Transfer. ICML Takeshi Teshima, Issei Sato, Masashi Sugiyama
2020	J	`jnl`	Few-shot Domain Adaptation by Causal Mechanism Transfer. CoRR Takeshi Teshima, Issei Sato, Masashi Sugiyama
2020	J	`jnl`	Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation. CoRR Masahiro Kato, Takeshi Teshima
2020	J	`jnl`	Universal Approximation Property of Neural Ordinary Differential Equations. CoRR Takeshi Teshima, Koichi Tojo, Masahiro Ikeda, Isao Ishikawa, Kenta Oono
2020	J	`jnl`	γ-ABC: Outlier-Robust Approximate Bayesian Computation based on Robust Divergence Estimator. CoRR Masahiro Fujisawa, Takeshi Teshima, Issei Sato
2019	A*	`conf`	Clipped Matrix Completion: A Remedy for Ceiling Effects. AAAI Takeshi Teshima, Miao Xu, Issei Sato, Masashi Sugiyama
2019	—	`conf`	Learning from Positive and Unlabeled Data with a Selection Bias. ICLR (Poster) Masahiro Kato, Takeshi Teshima, Junya Honda
2018	J	`jnl`	Clipped Matrix Completion: a Remedy for Ceiling Effects. CoRR Takeshi Teshima, Miao Xu, Issei Sato, Masashi Sugiyama