研究業績

Y. Giga, J. Okamoto, K. Sakakibara, and M. Uesaka
On a singular limit of the Kobayashi−Warren−Carter energy
accepted by Indiana University Mathematics Journal (arXiv:2205.14314)

K. Sakakibara and Y. Shimizu
Numerical analysis of the Plateau problem by the method of fundamental solutions
Journal of Scientific Computing 100 (2024), article number 2, 20 pp. (DOI: 10.1007/s10915-024-02551-z)

M. Nagayama, H. Monobe, K. Sakakibara, K.-I. Nakamura, Y. Kobayashi, and H. Kitahata
On the reaction-diffusion type modelling of the self-propelled object motion
Scientific Reports 13 (2023), 12633, 10 pp. (DOI: 10.1038/s41598-023-39395-w)

K. Sakakibara, Y. Shimoji, and S. Yazaki
A simple numerical method for Hele-Shaw type problems by the method of fundamental solutions
Japan Journal of Industrial and Applied Mathematics 39 (2022), no. 3, 869--887 (Special Issue on Czech-Japanese Seminar in Applied Mathematics 2021 (CJS2021), DOI: 10.1007/s13160-022-00530-1)

H. Matano, Y. Mori, M. Nara, and K. Sakakibara
Asymptotic behavior of fronts and pulses of the bidomain model
SIAM Journal on Applied Dynamical Systems 21 (2022), no. 1, 616--649. (DOI: 10.1137/21M1416904)

K. Sakakibara
Numerical analysis of constrained total variation flows
Advanced Studies in Pure Mathematics 85 (2020), 349--358. (DOI: 10.2969/aspm/08510349)

K. Sakakibara and Y. Miyatake
A fully discrete curve-shortening polygonal evolution law for moving boundary problems
Journal of Computational Physics 424 (2021), 109857, 22 pp. (DOI: 10.1016/j.jcp.2020.109857)

Y. Giga, K. Sakakibara, K. Taguchi, and M. Uesaka
A new numerical scheme for discrete constrained total variation flows and its convergence
Numerische Mathematik 146 (2020), 181--217. (DOI: 10.1007/s00211-020-01134-y)

K. Sakakibara
Bidirectional numerical conformal mapping based on the dipole simulation method
Engineering Analysis with Boundary Elements 114 (2020), 45--57. (DOI: 10.1016/j.enganabound.2020.01.009)

K. Sakakibara and S. Yazaki
Structure-preserving numerical scheme for the one-phase Hele-Shaw problems by the method of fundamental solutions
Computational and Mathematical Methods 1 (2019), no. 6, 25 pp. (DOI: 10.1002/cmm4.1063）

K.-I. Nakamura, K. Sakakibara, and S. Yazaki
Numerical approach to three-dimensional model of cellular electrophysiology by the method of fundamental solutions
JSIAM Letters 11 (2019), 17--20. (DOI: 10.14495/jsiaml.11.17)

K. Sakakibara
Method of fundamental solutions for biharmonic equation based on Almansi-type decomposition
Applications of Mathematics 62 (2017), no. 4, 297--317. (DOI: 10.21136/AM.2017.0018-17)

K. Sakakibara and S. Yazaki
Method of fundamental solutions with weighted average condition and dummy points
JSIAM Letters 9 (2017), 41--44. (DOI: 10.14495/jsiaml.9.41)

K. Sakakibara and S. Yazaki
On invariance of schemes in the method of fundamental solutions
Applied Mathematics Letters 73 (2017), 16--21. (DOI: 10.1016/j.aml.2017.04.018)

K. Sakakibara
Asymptotic analysis of the conventional and invariant schemes for the method of fundamental solutions applied to potential problems in doubly-connected regions
Japan Journal of Industrial and Applied Mathematics, 34 (2017), no. 1, 177--228 (DOI: 10.1007/s13160-017-0241-4)

K. Sakakibara
Analysis of the dipole simulation method for two-dimensional Dirichlet problems in Jordan regions with analytic boundaries
BIT Numerical Mathematics 56 (2016), no. 4, 1369--1400. (DOI: 10.1007/s10543-016-0605-1)

K. Sakakibara and M. Katsurada
A Mathematical Analysis of the Complex Dipole Simulation Method
Tokyo Journal of Mathematics 38 (2015), no. 2, 309--326 (DOI: 10.3836/tjm/1452806041)

Y. Hashimoto, S. Sonoda, I. Ishikawa, A. Nitanda, and T. Suzuki
Koopman-based generalization bound: New aspect for full-rank weights
Accepted for International Conference on Learning Representations (ICLR) (2024)  (URL: https://openreview.net/forum?id=JN7TcCm9LF)

Y. Hashimoto, M. Ikeda, and H. Kadri
Deep learning with kernels through RKHM and the Perron-Frobenius operator
Conference on Neural Information Processing Systems (NeurIPS) (2023) (URL: https://openreview.net/forum?id=3ZrGmenVM2)

S. Sonoda, Y. Hashimoto, I. Ishikawa, and M. Ikeda
Deep Ridgelet Transform: Voice with Koopman Operator Proves Universality of Formal Deep Networks
NeurIPS Workshop on Symmetry and Geometry in Neural Representations (2023) (URL: https://openreview.net/forum?id=2EuaV9an6m)

Y. Hashimoto, F. Komura, and M. Ikeda
Hilbert C*-module for structured data analysis
Matrix and Operator Equations and Applications (2023) (DOI: 10.1007/16618_2023_58)

Y. Hashimoto, M. Ikeda, and H. Kadri
Learning in RKHM: a C*-algebraic twist for kernel machines
International Conference on Artificial Intelligence and Statistics (AISTATS) (2023) (URL: https://proceedings.mlr.press/v206/hashimoto23a.html)

Y. Hashimoto, Z. Wang, and T. Matsui
C*-algebra net: a new approach generalizing neural network parameters to C*-algebra
International Conference on Machine Learning (ICML) (2022) (URL: https://proceedings.mlr.press/v162/hashimoto22a.html)

Y. Hashimoto and T. Nodera
A preconditioning technique for Krylov subspace methods in RKHSs
Journal of Computational and Applied Mathematics 415 (2022), 114490 (DOI: 10.1016/j.cam.2022.114490)

Y. Hashimoto, I. Ishikawa, M. Ikeda, F. Komura, T. Katsura, and Y. Kawahara
Reproducing kernel Hilbert C*-module and kernel mean embeddings
Journal of Machine Learning Research 22 (2021), no. 267, 1--56 (URL: https://www.jmlr.org/papers/v22/20-1346.html)

Y. Hashimoto and T. Nodera
Krylov subspace methods for estimating operator-vector multiplications in Hilbert spaces
Japan Journal of Industrial and Applied Mathematics 38 (2021), 781--803 (DOI: 10.1007/s13160-021-00460-4)

Y. Hashimoto and T. Nodera
Inexact Rational Krylov Method for Evolution Equations
BIT Numerical Mathematics 61 (2021), 473--502 (DOI: 10.1007/s10543-020-00829-w)

Y. Hashimoto, I. Ishikawa, M. Ikeda, Y. Matsuo, and Y. Kawahara
Krylov Subspace Method for Nonlinear Dynamical Systems with Random Noise
Journal of Machine Learning Research 21 (2020), no. 172, 1--29 (URL: https://www.jmlr.org/papers/v21/19-993.html)

Y. Hashimoto and T. Nodera
Shift-invert Rational Krylov method for an operator φ-function of an unbounded linear operator
Japan Journal of Industrial and Applied Mathematics 36 (2019), 421--433 (DOI: 10.1007/s13160-019-00347-5)

I. Ishikawa, K. Fujii, M. Ikeda, Y. Hashimoto, and Y. Kawahara
Metric on Nonlinear Dynamical Systems with Koopman Operators
Conference on Neural Information Processing Systems (NeurIPS) (2018) (URL: https://papers.nips.cc/paper_files/paper/2018/hash/fa1e9c965314ccd7810fb5ea838303e5-Abstract.html)

Y. Hashimoto and T. Nodera
Double-shift-invert Arnoldi method for computing the matrix exponential
Japan Journal of Industrial and Applied Mathematics 35 (2018), 727--738 (DOI: 10.1007/s13160-018-0309-9)

Y. Hashimoto and T. Nodera
Shift-invert Rational Krylov Method for Evolution Equation
Computational Techniques and Applications Conference, ANZIAM Journal 58 (2017), C149--C161 (DOI: 10.21914/anziamj.v58i0.11622)

Y. Hashimoto，T. Nodera
Inexact Shift-invert Arnoldi Method for Evolution Equation
ANZIAM Journal 58 (2016)，E1--E2 (DOI: 10.21914/anziamj.v58i0.10766)

橋本悠香，野寺隆
線形発展方程式のための Inexact Shift-invert Arnoldi 法
情報処理学会論文誌 57 (2016)，no. 10，2250--2259 (URL: http://id.nii.ac.jp/1001/00175021/)

K. Ishii, Y. Kohsaka, N. Miyake, and K. Sakakibara
A threshold-type algorithm to the gradient flow of the Canham-Helfrich functional
arXiv:2311.13155

K. Morikuni, K. Sakakibara, and A. Takatsu
Error estimate for regularized optimal transport problems via Bregman divergence
arXiv:2309.11666

Y. Giga, A. Kubo, H. Kuroda, J. Okamoto, K. Sakakibara and M. Uesaka
Fractional time differential equations as a singular limit of the Kobayashi–Warren–Carter system
arXiv:2306.15235

榊原 航也
基本解近似解法の現状
日本数学会「数学」

T. Kemmochi, Y. Miyatake, and K. Sakakibara
Structure-preserving numerical methods for constrained gradient flows of planar curves with explicit tangential velocities
arXiv:2208.00675

D. Giannakis, Y. Hashimoto, M. Ikeda, I. Ishikawa, and J. Slawinska
Koopman spectral analysis of skew-product dynamics on Hilbert C*-modules
arXiv:2307.08965

R. Hataya and Y. Hashimoto
Noncommutative C*-algebra Net: Learning Neural Networks with Powerful Product Structure in C*-algebra
arXiv: 2302.01191