Razmik Arman Khosrovian, Takaharu Yaguchi, Takashi Matsubara. Port-Hamiltonian Neural Networks for Learning Coupled Systems and Their Interactions. NeurIPS 2024 Workshop on Machine Learning and the Physical Sciences. 2024
Yosuke Nishimoto, Takashi Matsubara. Transformer-based Imagination with Slot Attention. NeurIPS 2024 Workshop on Compositional Learning. 2024
Keigo Tsutsui, Phuoc Thanh Tran-Ngoc, Hirotaka Sato, Takashi Matsubara. Deep Dynamics Modeling of Interactions in Collective Behaviors of Insects. Proc. of 2024 International Symposium on Nonlinear Theory and Its Applications (NOLTA2024). 2024
Takashi Matsubara, Yuto Miyatake, Takaharu Yaguchi. The Symplectic Adjoint Method: Memory-Efficient Backpropagation of Neural-Network-Based Differential Equations. IEEE Transactions on Neural Networks and Learning Systems. 2024. 35. 8. 10526-10538
Takahito Yoshida, Takaharu Yaguchi, Takashi Matsubara. Loss Function for Deep Learning to Model Dynamical Systems. IEICE Transactions on Information and Systems. 2024. vol. E107-D. no. 11
Learning the Dynamics and Connectivity of Coupled Systems via Port-Hamiltonian Neural Networks
(REMODEL-DSC Workshop on Machine Learning and Physics 2024)
Operator Learning of Hamiltonian Density for Modeling Nonlinear Waves
(International Conference on Scientific Computation and Differential Equations (SciCADE) 2024)
2019/01 - The 7th Japan-Korea Joint Workshop on Complex Communication Sciences (JKCCS) Best Paper Award Image-Caption Retrieval with Evaluating Uncertainties