Naoya Takeishi

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 44

Top Topics

Dimensionality Reduction

Generative Model

Top Venues

Publications

Maciej Falkiewicz, Naoya Takeishi, Alexandros Kalousis
Kolmogorov-Smirnov GAN. CoRR (2024)
Keisuke Fujii, Kazushi Tsutsui, Atom Scott, Hiroshi Nakahara, Naoya Takeishi, Yoshinobu Kawahara
Adaptive Action Supervision in Reinforcement Learning from Real-World Multi-Agent Demonstrations. ICAART (2) (2024)
Keisuke Fujii, Naoya Takeishi, Yoshinobu Kawahara, Kazuya Takeda
Decentralized policy learning with partial observation and mechanical constraints for multiperson modeling. Neural Networks 171 (2024)
João A. Cândido Ramos, Lionel Blondé, Naoya Takeishi, Alexandros Kalousis
Sample-Efficient On-Policy Imitation Learning from Observations. CoRR (2023)
Naoya Takeishi, Yoshinobu Kawahara
A Characteristic Function for Shapley-Value-Based Attribution of Anomaly Scores. Trans. Mach. Learn. Res. 2023 (2023)
Naoya Takeishi, Alexandros Kalousis
Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models. AISTATS (2023)
Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis
Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability. NeurIPS (2023)
Keisuke Fujii, Kazushi Tsutsui, Atom Scott, Hiroshi Nakahara, Naoya Takeishi, Yoshinobu Kawahara
Adaptive action supervision in reinforcement learning from real-world multi-agent demonstrations. CoRR (2023)
Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis
Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability. CoRR (2023)
Naoya Takeishi, Alexandros Kalousis
Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models. CoRR (2022)
Naoya Takeishi, Keisuke Fujii, Koh Takeuchi, Yoshinobu Kawahara
Discriminant Dynamic Mode Decomposition for Labeled Spatiotemporal Data Collections. SIAM J. Appl. Dyn. Syst. 21 (2) (2022)
Keisuke Fujii, Koh Takeuchi, Atsushi Kuribayashi, Naoya Takeishi, Yoshinobu Kawahara, Kazuya Takeda
Estimating counterfactual treatment outcomes over time in multi-vehicle simulation. SIGSPATIAL/GIS (2022)
Keisuke Fujii, Koh Takeuchi, Atsushi Kuribayashi, Naoya Takeishi, Yoshinobu Kawahara, Kazuya Takeda
Estimating counterfactual treatment outcomes over time in complex multi-agent scenarios. CoRR (2022)
Naoya Takeishi, Alexandros Kalousis
Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling. NeurIPS (2021)
Naoya Takeishi, Yoshinobu Kawahara
Learning Dynamics Models with Stable Invariant Sets. AAAI (2021)
Naoya Ozaki, Kanta Yanagida, Takuya Chikazawa, Nishanth Pushparaj, Naoya Takeishi, Ryuki Hyodo
Asteroid Flyby Cycler Trajectory Design Using Deep Neural Networks. CoRR (2021)
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
Learning interaction rules from multi-animal trajectories via augmented behavioral models. CoRR (2021)
Naoya Takeishi, Keisuke Fujii, Koh Takeuchi, Yoshinobu Kawahara
Discriminant Dynamic Mode Decomposition for Labeled Spatio-Temporal Data Collections. CoRR (2021)
Naoya Takeishi, Alexandros Kalousis
Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling. CoRR (2021)
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
Learning interaction rules from multi-animal trajectories via augmented behavioral models. NeurIPS (2021)
Naoya Takeishi, Yoshinobu Kawahara
Knowledge-Based Regularization in Generative Modeling. IJCAI (2020)
Keisuke Fujii, Naoya Takeishi, Yoshinobu Kawahara, Kazuya Takeda
Policy learning with partial observation and mechanical constraints for multi-person modeling. CoRR (2020)
Naoya Takeishi, Yoshinobu Kawahara
On Anomaly Interpretation via Shapley Values. CoRR (2020)
Naoya Takeishi, Yoshinobu Kawahara
Learning Multiple Nonlinear Dynamical Systems with Side Information. CDC (2020)
Naoya Takeishi, Yoshinobu Kawahara
Learning Dynamics Models with Stable Invariant Sets. CoRR (2020)
Anand Srinivasan, Naoya Takeishi
An MCMC Method for Uncertainty Set Generation via Operator-Theoretic Metrics. CDC (2020)
Naoya Takeishi
Shapley Values of Reconstruction Errors of PCA for Explaining Anomaly Detection. CoRR (2019)
Naoya Takeishi
Kernel Learning for Data-Driven Spectral Analysis of Koopman Operators. ACML (2019)
Riku Sasaki, Naoya Takeishi, Takehisa Yairi, Koichi Hori
Neural Gray-Box Identification of Nonlinear Partial Differential Equations. PRICAI (2) (2019)
Keisuke Fujii, Naoya Takeishi, Motokazu Hojo, Yuki Inaba, Yoshinobu Kawahara
Physically-interpretable classification of network dynamics for complex collective motions. CoRR (2019)
Naoya Takeishi, Yoshinobu Kawahara
Regularizing Generative Models Using Knowledge of Feature Dependence. CoRR (2019)
Naoya Takeishi
Shapley Values of Reconstruction Errors of PCA for Explaining Anomaly Detection. ICDM Workshops (2019)
Naoya Takeishi, Takehisa Yairi, Yoshinobu Kawahara
Factorially Switching Dynamic Mode Decomposition for Koopman Analysis of Time-Variant Systems. CDC (2018)
Rem Hida, Naoya Takeishi, Takehisa Yairi, Koichi Hori
Dynamic and Static Topic Model for Analyzing Time-Series Document Collections. ACL (2) (2018)
Naoya Takeishi, Kosuke Akimoto
Knowledge-Based Distant Regularization in Learning Probabilistic Models. CoRR (2018)
Rem Hida, Naoya Takeishi, Takehisa Yairi, Koichi Hori
Dynamic and Static Topic Model for Analyzing Time-Series Document Collections. CoRR (2018)
Naoya Takeishi, Yoshinobu Kawahara, Yasuo Tabei, Takehisa Yairi
Bayesian Dynamic Mode Decomposition. IJCAI (2017)
Naoya Takeishi, Takehisa Yairi
Visual Monocular Localization, Mapping, and Motion Estimation of a Rotating Small Celestial Body. J. Robotics Mechatronics 29 (5) (2017)
Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi
Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition. CoRR (2017)
Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi
Sparse nonnegative dynamic mode decomposition. ICIP (2017)
Takehisa Yairi, Naoya Takeishi, Tetsuo Oda, Yuta Nakajima, Naoki Nishimura, Noboru Takata
A Data-Driven Health Monitoring Method for Satellite Housekeeping Data Based on Probabilistic Clustering and Dimensionality Reduction. IEEE Trans. Aerosp. Electron. Syst. 53 (3) (2017)
Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi
Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition. NIPS (2017)
Chun Fui Liew, Danielle DeLatte, Naoya Takeishi, Takehisa Yairi
Recent Developments in Aerial Robotics: A Survey and Prototypes Overview. CoRR (2017)
Naoya Takeishi, Takehisa Yairi, Naoki Nishimura, Yuta Nakajima, Noboru Takata
Dynamic Grouped Mixture Models for Intermittent Multivariate Sensor Data. PAKDD (2) (2016)
Naoya Takeishi, Takehisa Yairi, Yuichi Tsuda, Fuyuto Terui, Naoko Ogawa, Yuya Mimasu
Simultaneous estimation of shape and motion of an asteroid for automatic navigation. ICRA (2015)
Naoya Takeishi, Takehisa Yairi
Anomaly detection from multivariate time-series with sparse representation. SMC (2014)
Akira Tanimoto, Naoya Takeishi, Takehisa Yairi, Yuichi Tsuda, Fuyuto Terui, Naoko Ogawa, Yuya Mimasu
Fast estimation of asteroid shape and motion for spacecraft navigation. ROBIO (2013)