Takeishi, Naoya

13 publications

NeurIPS 2025 A Temporal Difference Method for Stochastic Continuous Dynamics Haruki Settai, Naoya Takeishi, Takehisa Yairi

ICML 2024 Mimicking Better by Matching the Approximate Action Distribution Joao Candido Ramos, Lionel Blondé, Naoya Takeishi, Alexandros Kalousis

TMLR 2023 A Characteristic Function for Shapley-Value-Based Attribution of Anomaly Scores Naoya Takeishi, Yoshinobu Kawahara

NeurIPS 2023 Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis

AISTATS 2023 Deep Grey-Box Modeling with Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models Naoya Takeishi, Alexandros Kalousis

AAAI 2021 Learning Dynamics Models with Stable Invariant Sets Naoya Takeishi, Yoshinobu Kawahara

NeurIPS 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

NeurIPS 2021 Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling Naoya Takeishi, Alexandros Kalousis

NeurIPSW 2021 Variational Autoencoder with Differentiable Physics Engine for Human Gait Analysis and Synthesis Naoya Takeishi, Alexandros Kalousis

IJCAI 2020 Knowledge-Based Regularization in Generative Modeling Naoya Takeishi, Yoshinobu Kawahara

ACML 2019 Kernel Learning for Data-Driven Spectral Analysis of Koopman Operators Naoya Takeishi

IJCAI 2017 Bayesian Dynamic Mode Decomposition Naoya Takeishi, Yoshinobu Kawahara, Yasuo Tabei, Takehisa Yairi

NeurIPS 2017 Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi