Yoshinobu Kawahara

发表

Analyzing relationships among ARMA processes based on non-Gaussianity of external influences

Yoshinobu Kawahara, Takashi Washio, Shohei Shimizu, 2011, Neurocomputing.

A Quadratic Actor Network for Model-Free Reinforcement Learning pdf

Yoshinobu Kawahara, Matthias Weissenbacher, Yoshinobu Kawahara, 2021, ArXiv.

Active Change-Point Detection

Shogo Hayashi, Hisashi Kashima, Yoshinobu Kawahara, 2019, ACML.

Principal points analysis via p-median problem for binary data

Yoshinobu Kawahara, Haruka Yamashita, 2019, Journal of applied statistics.

Structured regularizer for spatio-temporal matrix completion 竹内孝

Tomoharu Iwata, Yoshinobu Kawahara, Koh Takeuchi, 2016 .

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

Yoshinobu Kawahara, Keisuke Fujii, Koh Takeuchi, 2022, 2206.01900.

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

Yoshinobu Kawahara, Keisuke Fujii, Koh Takeuchi, 2022, ArXiv.

A newly designed and constructed 20 kHz magnetic field exposure facility for in vivo study

K. Yamazaki, A. Haga, Yoshinobu Kawahara, 2009, Bioelectromagnetics.

Estimating counterfactual treatment outcomes over time in multi-vehicle simulation

Yoshinobu Kawahara, Keisuke Fujii, Koh Takeuchi, 2022, SIGSPATIAL/GIS.

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

Yoshinobu Kawahara, Keisuke Fujii, Naoya Takeishi, 2020, ArXiv.

Predicting behavior through dynamic modes in resting-state fMRI data

Yoshinobu Kawahara, S. Ikeda, O. Yamashita, 2021, NeuroImage.

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

Yoshinobu Kawahara, Naoya Takeishi, Shizuko Hiryu, 2021, NeurIPS.

Dynamic Mode Decomposition via Dictionary Learning for Foreground Modeling in Videos

Yoshinobu Kawahara, Keisuke Fujii, Israr Ul Haq, 2020, VISIGRAPP.

Neural decoding of electrocorticographic signals using dynamic mode decomposition

Haruhiko Kishima, Youichi Saitoh, Shota Yamamoto, 2020, Journal of neural engineering.

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

Yoshinobu Kawahara, Naoya Takeishi, Keisuke Fujii, 2021, SIAM J. Appl. Dyn. Syst..

Meta-Learning for Koopman Spectral Analysis with Short Time-series

Tomoharu Iwata, Yoshinobu Kawahara, 2021, ArXiv.

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

Yoshinobu Kawahara, Keisuke Fujii, Yuki Inaba, 2019, Scientific Reports.

ynamic mode decomposition via dictionary learning for foreground odeling in videos

Yoshinobu Kawahara, Keisuke Fujii, S. Haq, 2020 .

Adaptive action supervision in reinforcement learning from real-world multi-agent demonstrations

Yoshinobu Kawahara, Keisuke Fujii, Naoya Takeishi, 2023, Proceedings of the 16th International Conference on Agents and Artificial Intelligence.

Dynamic mode decomposition via convolutional autoencoders for dynamics modeling in videos

Tomoharu Iwata, Yoshinobu Kawahara, I. Haq, 2022, Comput. Vis. Image Underst..

UNIVERSAL MODAL EMBEDDING OF DYNAMICS IN VIDEOS AND ITS APPLICATIONS

Yoshinobu Kawahara, Israr Ul Haq, Yoshinobu Kawahara, 2019 .

A Characteristic Function for Shapley-Value-Based Attribution of Anomaly Scores

Yoshinobu Kawahara, Naoya Takeishi, 2020, 2004.04464.

Manifold alteration between major depressive disorder and healthy control subjects using dynamic mode decomposition in resting-state fMRI data

Yoshinobu Kawahara, H. Yamagata, Kenichiro Harada, 2024, Frontiers in Psychiatry.

Decentralized policy learning with partial observation and mechanical constraints for multiperson modeling

K. Takeda, Yoshinobu Kawahara, Keisuke Fujii, 2020, Neural Networks.

Glocal Hypergradient Estimation with Koopman Operator

Yoshinobu Kawahara, Ryuichiro Hataya, 2024, ArXiv.

The Disappearance of Timestep Embedding in Modern Time-Dependent Neural Networks

Bum Jun Kim, Yoshinobu Kawahara, Sang Woo Kim, 2024, 2405.14126.