Talks | Publications | Structured Artificial Intelligence Lab., Faculty of Information Science and Technology, Hokkaido University

Inveted Talks

Takashi Matsubara, "Deep Learning-based Modeling Inspired by Geometric Mechanics," Workshop on Dynamical Systems and Machine Learning, Tokyo, 17 Feb. 2025. link

Takashi Matsubara, "Deep Learning Meets Geometric Mechanics," CAI 2024 Workshop on Scientific Machine Learning and Its Industrial Applications (SMLIA2024), Singapore, Jun. 2024. link
Takashi Matsubara, "Deep Geometric Mechanics: From Hamiltonian Neural Networks to Discrete-Time Physics and Beyond," International Conference on Scientific Computing and Machine Learning (SCML), Kyoto, Mar. 2024. link

Razmik Arman Khosrovian, Takaharu Yaguchi, and Takashi Matsubara, "Learning the Dynamics and Connectivity of Coupled Systems via Port-Hamiltonian Neural Networks," REMODEL-DSC Workshop on Machine Learning and Physics, Sapporo, 31 Aug. 2024. link
Baige Xu, Yusuke Tanaka, Takashi Matsubara, Takaharu Yaguchi, "Operator Learning of Hamiltonian Density for Modeling Nonlinear Waves," International Conference on Scientific Computation and Differential Equations (SciCADE), Singapore, 18 Jul. 2024.
Takashi Matsubara, Takaharu Yaguchi, "An error bound of PINNs for solving differential equations," International Conference on Scientific Computation and Differential Equations (SciCADE), Singapore, 15 Jul. 2024.

Takashi Matsubara, "Geometric Deep Learning for Modeling Dynamical Systems and Incorporating Laws of Physics," Tutorial 02 New Trends in Machine Learning for Science and Engineering at 2023 SICE Annual Conference (SICE), Tsu, Sep. 2023. link
Takehiro Aoshima and Takashi Matsubara, "Deep Curvilinear Editing: Commutative and Nonlinear Image Manipulation for Pretrained Deep Generative Model," 第26回画像の認識・理解シンポジウム (MIRU2023), 浜松, 7月, 2023.
Takashi Matsubara, "Geometric and Bayesian Deep Learning for Incorporating Our Needs," Japanese-Canadian Frontiers of Science (JCFoS) Symposium, Mar. 2023, . link

Yuhan Chen, Takashi Matsubara, and Takaharu Yaguchi, "Geometric Integrators for Neural Symplectic Forms," 10th International Congress on Industrial and Applied Mathematics (ICIAM2023), Tokyo, Aug. 2023.
Baige Xu, Yuhan Chen, Takashi Matsubara, Takaharu Yaguchi, "Structure-Preserving Learning for GENERIC systems," 10th International Congress on Industrial and Applied Mathematics (ICIAM2023), Tokyo, Aug. 2023.
Taisei Ueda, Takashi Matsubara, Takaharu Yaguchi, "Application of the Kernel Method to Learning Hamiltonian Equations," 10th International Congress on Industrial and Applied Mathematics (ICIAM2023), Tokyo, Aug. 2023.

Takashi Matsubara, Yuhan Chen, Takaharu Yaguchi (speaker), "Geometric Deep Energy-Based Models for Physics," Workshop on Functional Inference and Machine Intelligence (FIMI2022), Mar. 2022, .

Baige Xu, Yuhan Chen, Takashi Matsubara, Takaharu Yaguchi, "Learning GENERIC Systems Using Neural Symplectic Forms," International Conference on Scientific Computation and Differential Equations (SciCADE), Reykjavík, Jul. 2022.
Yuhan Chen, Takashi Matsubara, Takaharu Yaguchi, "Theoretical analysis of approximation properties of Hamiltonian neural networks," International Conference on Scientific Computation and Differential Equations (SciCADE), Reykjavík, Jul. 2022.
Yuhan Chen, Takashi Matsubara, Takaharu Yaguchi, "Neural symplectic form and coordinate-free learning of Hamiltonian dynamics," International Conference on Scientific Computation and Differential Equations (SciCADE), Reykjavík, Jul. 2022.

Kimiaki Shirahama, Takumi Sato, Norihiro Yamawaki, Takashi Matsubara, Kuniaki Uehara, "Kindai University and Osaka Gakuin University and Osaka University at TRECVID 2021 AVS Tasks," TREC Video Retrieval Evaluation (TRECVID), Virtual, Nov. 2021.

Daiki Mukai, Ryosuke Utsunomiya, Shunsuke Utsuki, Kimiaki Shirahama, Takashi Matsubara, and Kuniaki Uehara, "Kindai University and Osaka Gakuin University at TRECVID 2020 AVS and ActEV Tasks," TREC Video Retrieval Evaluation (TRECVID), Virtual, Nov. 2020.

Takashi Matsubara, "Deep Learning Regularized by Structure and Hierarchy," The 7th Japan-Korea Joint Workshop on Complex Communication Sciences (JKCCS), Pyengonchang, Jan. 2019.

Kimiaki Shirahama, Daichi Sakurai, Takashi Matsubara, Kuniaki Uehara, "Kindai University and Kobe University at TRECVID 2019 AVS Task," TREC Video Retrieval Evaluation (TRECVID), Gaithersburg, Nov. 2019.

Takashi Matsubara, "Neural Generative Model of Small Dataset for Leveraging Our Knowledge," The 2nd NTU-Kobe U Joint Workshop 2018, Data Science and Artificial Intelligence, Singapore, Mar. 2018.

Takashi Matsubara, "Artificial Neural Networks with Domain-Knowledge," The 7th Kobe University Brussels European Center Symposium, Brussels, Nov. 2016.

Takashi Matsubara and Hiroyuki Torikai, "Asynchronous Cellular Automaton Based Neuron and its Reproduction Capability of Neuron-like Responses," Kyoto Workshop on NOLTA, Kyoto, Nov. 2011.