Yaguchi, Takaharu

13 publications

AISTATS 2025 Energy-Consistent Neural Operators for Hamiltonian and Dissipative Partial Differential Equations Yusuke Tanaka, Takaharu Yaguchi, Tomoharu Iwata, Naonori Ueda

AAAI 2025 Number Theoretic Accelerated Learning of Physics-Informed Neural Networks Takashi Matsubara, Takaharu Yaguchi

ICLR 2025 Poisson-Dirac Neural Networks for Modeling Coupled Dynamical Systems Across Domains Razmik Arman Khosrovian, Takaharu Yaguchi, Hiroaki Yoshimura, Takashi Matsubara

NeurIPS 2025 UEPI: Universal Energy-Behavior-Preserving Integrators for Energy Conservative/Dissipative Differential Equations Elena Celledoni, Brynjulf Owren, Chong Shen, Baige Xu, Takaharu Yaguchi

NeurIPSW 2023 Algebraic Design of Physical Computing System for Time-Series Generation Mizuka Komatsu, Takaharu Yaguchi, Kohei Nakajima

ICMLW 2023 Equivalence Class Learning for GENERIC Systems Baige Xu, Yuhan Chen, Takashi Matsubara, Takaharu Yaguchi

ICLR 2023 FINDE: Neural Differential Equations for Finding and Preserving Invariant Quantities Takashi Matsubara, Takaharu Yaguchi

ICMLW 2023 Good Lattice Accelerates Physics-Informed Neural Networks Takashi Matsubara, Takaharu Yaguchi

ICMLW 2023 Variational Principle and Variational Integrators for Neural Symplectic Forms Yuhan Chen, Baige Xu, Takashi Matsubara, Takaharu Yaguchi

AAAI 2022 KAM Theory Meets Statistical Learning Theory: Hamiltonian Neural Networks with Non-Zero Training Loss Yuhan Chen, Takashi Matsubara, Takaharu Yaguchi

NeurIPS 2021 Neural Symplectic Form: Learning Hamiltonian Equations on General Coordinate Systems Yuhan Chen, Takashi Matsubara, Takaharu Yaguchi

NeurIPS 2021 Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory Takashi Matsubara, Yuto Miyatake, Takaharu Yaguchi

NeurIPS 2020 Deep Energy-Based Modeling of Discrete-Time Physics Takashi Matsubara, Ai Ishikawa, Takaharu Yaguchi