Naoya Takeishi

According to our database, Naoya Takeishi authored at least 35 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Adaptive Action Supervision in Reinforcement Learning from Real-World Multi-Agent Demonstrations.

Keisuke Fujii, Kazushi Tsutsui, Atom Scott, Hiroshi Nakahara, Naoya Takeishi, Yoshinobu Kawahara

Proceedings of the 16th International Conference on Agents and Artificial Intelligence, 2024

2023

Sample-Efficient On-Policy Imitation Learning from Observations.

João A. Cândido Ramos, Lionel Blondé, Naoya Takeishi, Alexandros Kalousis

CoRR, 2023

Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability.

Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models.

Naoya Takeishi, Alexandros Kalousis

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Discriminant Dynamic Mode Decomposition for Labeled Spatiotemporal Data Collections.

Naoya Takeishi, Keisuke Fujii, Koh Takeuchi, Yoshinobu Kawahara

SIAM J. Appl. Dyn. Syst., 2022

Estimating counterfactual treatment outcomes over time in complex multi-agent scenarios.

Keisuke Fujii, Koh Takeuchi, Atsushi Kuribayashi, Naoya Takeishi, Yoshinobu Kawahara, Kazuya Takeda

CoRR, 2022

Estimating counterfactual treatment outcomes over time in multi-vehicle simulation.

Keisuke Fujii, Koh Takeuchi, Atsushi Kuribayashi, Naoya Takeishi, Yoshinobu Kawahara, Kazuya Takeda

Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022

2021

Asteroid Flyby Cycler Trajectory Design Using Deep Neural Networks.

Naoya Ozaki, Kanta Yanagida, Takuya Chikazawa, Nishanth Pushparaj, Naoya Takeishi, Ryuki Hyodo

CoRR, 2021

Discriminant Dynamic Mode Decomposition for Labeled Spatio-Temporal Data Collections.

Naoya Takeishi, Keisuke Fujii, Koh Takeuchi, Yoshinobu Kawahara

CoRR, 2021

Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling.

Naoya Takeishi, Alexandros Kalousis

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning interaction rules from multi-animal trajectories via augmented behavioral models.

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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Dynamics Models with Stable Invariant Sets.

Naoya Takeishi, Yoshinobu Kawahara

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Policy learning with partial observation and mechanical constraints for multi-person modeling.

Keisuke Fujii, Naoya Takeishi, Yoshinobu Kawahara, Kazuya Takeda

CoRR, 2020

On Anomaly Interpretation via Shapley Values.

Naoya Takeishi, Yoshinobu Kawahara

CoRR, 2020

Knowledge-Based Regularization in Generative Modeling.

Naoya Takeishi, Yoshinobu Kawahara

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Learning Multiple Nonlinear Dynamical Systems with Side Information.

Naoya Takeishi, Yoshinobu Kawahara

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

An MCMC Method for Uncertainty Set Generation via Operator-Theoretic Metrics.

Anand Srinivasan, Naoya Takeishi

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

2019

Physically-interpretable classification of network dynamics for complex collective motions.

Keisuke Fujii, Naoya Takeishi, Motokazu Hojo, Yuki Inaba, Yoshinobu Kawahara

CoRR, 2019

Regularizing Generative Models Using Knowledge of Feature Dependence.

Naoya Takeishi, Yoshinobu Kawahara

CoRR, 2019

Neural Gray-Box Identification of Nonlinear Partial Differential Equations.

Riku Sasaki, Naoya Takeishi, Takehisa Yairi, Koichi Hori

Proceedings of the PRICAI 2019: Trends in Artificial Intelligence, 2019

Shapley Values of Reconstruction Errors of PCA for Explaining Anomaly Detection.

Naoya Takeishi

Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

Kernel Learning for Data-Driven Spectral Analysis of Koopman Operators.

Naoya Takeishi

Proceedings of The 11th Asian Conference on Machine Learning, 2019

2018

Knowledge-Based Distant Regularization in Learning Probabilistic Models.

Naoya Takeishi, Kosuke Akimoto

CoRR, 2018

Factorially Switching Dynamic Mode Decomposition for Koopman Analysis of Time-Variant Systems.

Naoya Takeishi, Takehisa Yairi, Yoshinobu Kawahara

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Dynamic and Static Topic Model for Analyzing Time-Series Document Collections.

Rem Hida, Naoya Takeishi, Takehisa Yairi, Koichi Hori

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017

A Data-Driven Health Monitoring Method for Satellite Housekeeping Data Based on Probabilistic Clustering and Dimensionality Reduction.

Takehisa Yairi, Naoya Takeishi, Tetsuo Oda, Yuta Nakajima, Naoki Nishimura, Noboru Takata

IEEE Trans. Aerosp. Electron. Syst., 2017

Visual Monocular Localization, Mapping, and Motion Estimation of a Rotating Small Celestial Body.

Naoya Takeishi, Takehisa Yairi

J. Robotics Mechatronics, 2017

Recent Developments in Aerial Robotics: A Survey and Prototypes Overview.

Chun Fui Liew, Danielle DeLatte, Naoya Takeishi, Takehisa Yairi

CoRR, 2017

Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition.

Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Bayesian Dynamic Mode Decomposition.

Naoya Takeishi, Yoshinobu Kawahara, Yasuo Tabei, Takehisa Yairi

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Sparse nonnegative dynamic mode decomposition.

Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi

Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

2016

Dynamic Grouped Mixture Models for Intermittent Multivariate Sensor Data.

Naoya Takeishi, Takehisa Yairi, Naoki Nishimura, Yuta Nakajima, Noboru Takata

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2016

2015

Simultaneous estimation of shape and motion of an asteroid for automatic navigation.

Naoya Takeishi, Takehisa Yairi, Yuichi Tsuda, Fuyuto Terui, Naoko Ogawa, Yuya Mimasu

Proceedings of the IEEE International Conference on Robotics and Automation, 2015

2014

Anomaly detection from multivariate time-series with sparse representation.

Naoya Takeishi, Takehisa Yairi

Proceedings of the 2014 IEEE International Conference on Systems, Man, and Cybernetics, 2014

2013

Fast estimation of asteroid shape and motion for spacecraft navigation.

Akira Tanimoto, Naoya Takeishi, Takehisa Yairi, Yuichi Tsuda, Fuyuto Terui, Naoko Ogawa, Yuya Mimasu

Proceedings of the IEEE International Conference on Robotics and Biomimetics, 2013