Naoya Takeishi

57 papers A* 8A 1B 3C 1Journal 32Unranked 12

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Accurate Open-Loop Control of a Soft Continuum Robot Through Visually Learned Latent Representations. CoRR Henrik Krauss, Johann Licher, Naoya Takeishi, Annika Raatz, Takehisa Yairi
2026	J	`jnl`	Learning Deep Hybrid Models with Sharpness-Aware Minimization. CoRR Naoya Takeishi
2025	J	`jnl`	A Temporal Difference Method for Stochastic Continuous Dynamics. CoRR Haruki Settai, Naoya Takeishi, Takehisa Yairi
2025	J	`jnl`	Data-driven simulator of multi-animal behavior with unknown dynamics via offline and online reinforcement learning. CoRR Keisuke Fujii, Kazushi Tsutsui, Yu Teshima, Makoto Itoh, Naoya Takeishi, Nozomi Nishiumi, Ryoya Tanaka, Shunsuke Shigaki, Yoshinobu Kawahara
2025	B	`conf`	Deterministic and Stochastic Hybrid Modeling with Regularization. SMC Akira Osaka, Naoya Takeishi, Takehisa Yairi
2025	J	`jnl`	Estimating Counterfactual Treatment Outcomes Over Time in Complex Multiagent Scenarios. IEEE Trans. Neural Networks Learn. Syst. Keisuke Fujii, Koh Takeuchi, Atsushi Kuribayashi, Naoya Takeishi, Yoshinobu Kawahara, Kazuya Takeda
2025	J	`jnl`	Learning Visually Interpretable Oscillator Networks for Soft Continuum Robots from Video. CoRR Henrik Krauss, Johann Licher, Naoya Takeishi, Annika Raatz, Takehisa Yairi
2025	—	`conf`	Probabilistic Safety for Hard-to-Formalize Constraints via Conformal Neural CBFs. CDC Koki Hirano, Naoya Takeishi, Takehisa Yairi
2025	J	`jnl`	Simulation-Efficient Cosmological Inference with Multi-Fidelity SBI. CoRR Leander Thiele, Adrian E. Bayer, Naoya Takeishi
2024	—	`conf`	Adaptive Action Supervision in Reinforcement Learning from Real-World Multi-Agent Demonstrations. ICAART (2) Keisuke Fujii, Kazushi Tsutsui, Atom Scott, Hiroshi Nakahara, Naoya Takeishi, Yoshinobu Kawahara
2024	J	`jnl`	Decentralized policy learning with partial observation and mechanical constraints for multiperson modeling. Neural Networks Keisuke Fujii, Naoya Takeishi, Yoshinobu Kawahara, Kazuya Takeda
2024	J	`jnl`	Kolmogorov-Smirnov GAN. CoRR Maciej Falkiewicz, Naoya Takeishi, Alexandros Kalousis
2024	A*	`conf`	Mimicking Better by Matching the Approximate Action Distribution. ICML João A. Cândido Ramos, Lionel Blondé, Naoya Takeishi, Alexandros Kalousis
2023	J	`jnl`	A Characteristic Function for Shapley-Value-Based Attribution of Anomaly Scores. Trans. Mach. Learn. Res. Naoya Takeishi, Yoshinobu Kawahara
2023	J	`jnl`	Adaptive action supervision in reinforcement learning from real-world multi-agent demonstrations. CoRR Keisuke Fujii, Kazushi Tsutsui, Atom Scott, Hiroshi Nakahara, Naoya Takeishi, Yoshinobu Kawahara
2023	A*	`conf`	Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability. NeurIPS Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis
2023	J	`jnl`	Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability. CoRR Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis
2023	A	`conf`	Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models. AISTATS Naoya Takeishi, Alexandros Kalousis
2023	J	`jnl`	Sample-Efficient On-Policy Imitation Learning from Observations. CoRR João A. Cândido Ramos, Lionel Blondé, Naoya Takeishi, Alexandros Kalousis
2022	J	`jnl`	Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models. CoRR Naoya Takeishi, Alexandros Kalousis
2022	J	`jnl`	Discriminant Dynamic Mode Decomposition for Labeled Spatiotemporal Data Collections. SIAM J. Appl. Dyn. Syst. Naoya Takeishi, Keisuke Fujii, Koh Takeuchi, Yoshinobu Kawahara
2022	J	`jnl`	Estimating counterfactual treatment outcomes over time in complex multi-agent scenarios. CoRR Keisuke Fujii, Koh Takeuchi, Atsushi Kuribayashi, Naoya Takeishi, Yoshinobu Kawahara, Kazuya Takeda
2022	—	`conf`	Estimating counterfactual treatment outcomes over time in multi-vehicle simulation. SIGSPATIAL/GIS Keisuke Fujii, Koh Takeuchi, Atsushi Kuribayashi, Naoya Takeishi, Yoshinobu Kawahara, Kazuya Takeda
2021	J	`jnl`	Asteroid Flyby Cycler Trajectory Design Using Deep Neural Networks. CoRR Naoya Ozaki, Kanta Yanagida, Takuya Chikazawa, Nishanth Pushparaj, Naoya Takeishi, Ryuki Hyodo
2021	J	`jnl`	Discriminant Dynamic Mode Decomposition for Labeled Spatio-Temporal Data Collections. CoRR Naoya Takeishi, Keisuke Fujii, Koh Takeuchi, Yoshinobu Kawahara
2021	A*	`conf`	Learning Dynamics Models with Stable Invariant Sets. AAAI Naoya Takeishi, Yoshinobu Kawahara
2021	A*	`conf`	Learning interaction rules from multi-animal trajectories via augmented behavioral models. NeurIPS Keisuke Fujii, Naoya Takeishi, Kazushi Tsutsui, Emyo Fujioka, Nozomi Nishiumi, Ryoya Tanaka, Mika Fukushiro, Kaoru Ide, Hiroyoshi Kohno, Ken Yoda, Susumu Takahashi, Shizuko Hiryu, Yoshinobu Kawahara
2021	J	`jnl`	Learning interaction rules from multi-animal trajectories via augmented behavioral models. CoRR Keisuke Fujii, Naoya Takeishi, Kazushi Tsutsui, Emyo Fujioka, Nozomi Nishiumi, Ryoya Tanaka, Mika Fukushiro, Kaoru Ide, Hiroyoshi Kohno, Ken Yoda, Susumu Takahashi, Shizuko Hiryu, Yoshinobu Kawahara
2021	A*	`conf`	Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling. NeurIPS Naoya Takeishi, Alexandros Kalousis
2021	J	`jnl`	Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling. CoRR Naoya Takeishi, Alexandros Kalousis
2020	—	`conf`	An MCMC Method for Uncertainty Set Generation via Operator-Theoretic Metrics. CDC Anand Srinivasan, Naoya Takeishi
2020	A*	`conf`	Knowledge-Based Regularization in Generative Modeling. IJCAI Naoya Takeishi, Yoshinobu Kawahara
2020	J	`jnl`	Learning Dynamics Models with Stable Invariant Sets. CoRR Naoya Takeishi, Yoshinobu Kawahara
2020	—	`conf`	Learning Multiple Nonlinear Dynamical Systems with Side Information. CDC Naoya Takeishi, Yoshinobu Kawahara
2020	J	`jnl`	On Anomaly Interpretation via Shapley Values. CoRR Naoya Takeishi, Yoshinobu Kawahara
2020	J	`jnl`	Policy learning with partial observation and mechanical constraints for multi-person modeling. CoRR Keisuke Fujii, Naoya Takeishi, Yoshinobu Kawahara, Kazuya Takeda
2019	C	`conf`	Kernel Learning for Data-Driven Spectral Analysis of Koopman Operators. ACML Naoya Takeishi
2019	—	`conf`	Neural Gray-Box Identification of Nonlinear Partial Differential Equations. PRICAI (2) Riku Sasaki, Naoya Takeishi, Takehisa Yairi, Koichi Hori
2019	J	`jnl`	Physically-interpretable classification of network dynamics for complex collective motions. CoRR Keisuke Fujii, Naoya Takeishi, Motokazu Hojo, Yuki Inaba, Yoshinobu Kawahara
2019	J	`jnl`	Regularizing Generative Models Using Knowledge of Feature Dependence. CoRR Naoya Takeishi, Yoshinobu Kawahara
2019	—	`conf`	Shapley Values of Reconstruction Errors of PCA for Explaining Anomaly Detection. ICDM Workshops Naoya Takeishi
2019	J	`jnl`	Shapley Values of Reconstruction Errors of PCA for Explaining Anomaly Detection. CoRR Naoya Takeishi
2018	—	`conf`	Dynamic and Static Topic Model for Analyzing Time-Series Document Collections. ACL (2) Rem Hida, Naoya Takeishi, Takehisa Yairi, Koichi Hori
2018	J	`jnl`	Dynamic and Static Topic Model for Analyzing Time-Series Document Collections. CoRR Rem Hida, Naoya Takeishi, Takehisa Yairi, Koichi Hori
2018	—	`conf`	Factorially Switching Dynamic Mode Decomposition for Koopman Analysis of Time-Variant Systems. CDC Naoya Takeishi, Takehisa Yairi, Yoshinobu Kawahara
2018	J	`jnl`	Knowledge-Based Distant Regularization in Learning Probabilistic Models. CoRR Naoya Takeishi, Kosuke Akimoto
2017	J	`jnl`	A Data-Driven Health Monitoring Method for Satellite Housekeeping Data Based on Probabilistic Clustering and Dimensionality Reduction. IEEE Trans. Aerosp. Electron. Syst. Takehisa Yairi, Naoya Takeishi, Tetsuo Oda, Yuta Nakajima, Naoki Nishimura, Noboru Takata
2017	A*	`conf`	Bayesian Dynamic Mode Decomposition. IJCAI Naoya Takeishi, Yoshinobu Kawahara, Yasuo Tabei, Takehisa Yairi
2017	—	`conf`	Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition. NIPS Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi
2017	J	`jnl`	Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition. CoRR Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi
2017	J	`jnl`	Recent Developments in Aerial Robotics: A Survey and Prototypes Overview. CoRR Chun Fui Liew, Danielle DeLatte, Naoya Takeishi, Takehisa Yairi
2017	B	`conf`	Sparse nonnegative dynamic mode decomposition. ICIP Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi
2017	J	`jnl`	Visual Monocular Localization, Mapping, and Motion Estimation of a Rotating Small Celestial Body. J. Robotics Mechatronics Naoya Takeishi, Takehisa Yairi
2016	—	`conf`	Dynamic Grouped Mixture Models for Intermittent Multivariate Sensor Data. PAKDD (2) Naoya Takeishi, Takehisa Yairi, Naoki Nishimura, Yuta Nakajima, Noboru Takata
2015	A*	`conf`	Simultaneous estimation of shape and motion of an asteroid for automatic navigation. ICRA Naoya Takeishi, Takehisa Yairi, Yuichi Tsuda, Fuyuto Terui, Naoko Ogawa, Yuya Mimasu
2014	B	`conf`	Anomaly detection from multivariate time-series with sparse representation. SMC Naoya Takeishi, Takehisa Yairi
2013	—	`conf`	Fast estimation of asteroid shape and motion for spacecraft navigation. ROBIO Akira Tanimoto, Naoya Takeishi, Takehisa Yairi, Yuichi Tsuda, Fuyuto Terui, Naoko Ogawa, Yuya Mimasu