Testing properties of functions on finite groups. - Kenta Oono; Yuichi Yoshida (Random Struct. Algorithms, 2016)

Semi-supervised learning of hierarchical representations of molecules using neural message passing. - Hai Nguyen; Shin-ichi Maeda; Kenta Oono (CoRR, 2017)

Approximation and non-parametric estimation of ResNet-type convolutional neural networks. - Kenta Oono; Taiji Suzuki (ICML, 2019)

On Asymptotic Behaviors of Graph CNNs from Dynamical Systems Perspective. - Kenta Oono; Taiji Suzuki (CoRR, 2019)

Graph Residual Flow for Molecular Graph Generation. - Shion Honda; Hirotaka Akita; Katsuhiko Ishiguro; Toshiki Nakanishi; Kenta Oono (CoRR, 2019)

Graph Neural Networks Exponentially Lose Expressive Power for Node Classification. - Kenta Oono; Taiji Suzuki (ICLR, 2020)

Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural Networks. - Kenta Oono; Taiji Suzuki (NeurIPS, 2020)

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

Weisfeiler-Lehman Embedding for Molecular Graph Neural Networks. - Katsuhiko Ishiguro; Kenta Oono; Kohei Hayashi (CoRR, 2020)

Universal Approximation Property of Neural Ordinary Differential Equations. - Takeshi Teshima; Koichi Tojo; Masahiro Ikeda; Isao Ishikawa; Kenta Oono (CoRR, 2020)

Fast Estimation Method for the Stability of Ensemble Feature Selectors. - Rina Onda; Zhengyan Gao; Masaaki Kotera; Kenta Oono (CoRR, 2021)

Controlling Posterior Collapse by an Inverse Lipschitz Constraint on the Decoder Network. - Yuri Kinoshita; Kenta Oono; Kenji Fukumizu; Yuichi Yoshida; Shin-ichi Maeda (ICML, 2023)

TabRet: Pre-training Transformer-based Tabular Models for Unseen Columns. - Soma Onishi; Kenta Oono; Kohei Hayashi (CoRR, 2023)

Virtual Human Generative Model: Masked Modeling Approach for Learning Human Characteristics. - Kenta Oono; Nontawat Charoenphakdee; Kotatsu Bito; Zhengyan Gao; Yoshiaki Ota; Shoichiro Yamaguchi; Yohei Sugawara; Shin-ichi Maeda; Kunihiko Miyoshi; Yuki Saito; Koki Tsuda; Hiroshi Maruyama; et al. (CoRR, 2023)

Universal Approximation Property of Invertible Neural Networks. - Isao Ishikawa; Takeshi Teshima; Koichi Tojo; Kenta Oono; Masahiro Ikeda; Masashi Sugiyama (J. Mach. Learn. Res., 2023)