ジャーナル論文 / Journal
  1. Komura, F., "Submodules of normalisers in groupoid C*-algebras and discrete group coactions", Forum Math. 0(0), (2024).
  2. Hatano, N., Ikeda, M., Ishikawa, I., and Sawano, Y., "Global Universality of the Two-Layer Neural Network with the k-Rectified Linear Unit", J. Funct. Spaces 2024, 1–6, (2024).
  3. Takeuchi, D., and Tsushima, T., "Gauss sums and Van der Geer–Van der Vlugt curves", Bull. Lond. Math. Soc. 56(2), 602–623, (2023).
  4. Ikeda, M., Ishikawa, I., and Taniguchi, K., "Boundedness of composition operators on higher order Besov spaces in one dimension", Math. Ann., 1–24, (2023).
  5. Hamano, M., and Ikeda, M., "Scattering solutions to nonlinear Schrödinger equation with a long range potential", J. Math. Anal. Appl. 528(1), 127468, (2023).
  6. Chiba, H., Ikeda, M., and Ishikawa, I., "Generalized Eigenvalues of the Perron–Frobenius Operators of Symbolic Dynamical Systems", SIAM J. Appl. Dyn. Syst. 22(4), 2825–2855, (2023).
  7. Bannai, K., Hagihara, K., Yamada, K., and Yamamoto, S., "Canonical equivariant cohomology classes generating zeta values of totally real fields", Transactions of the American Mathematical Society Series B 10(19), 613–635, (2023).
  8. Tojo, K., and Yoshino, T., "A method to construct exponential families by representation theory", Inf. Geom. 5, 493–510, (2022).
  9. Takeuchi, D., "On Continuity of Local Epsilon Factors of l-adic Sheaves", International Mathematics Research Notices, (2022).
  10. Sekisaka-Yamamoto, H., "reaction-diffusion approximation of a semilinear wave equation with damping", Jpn. J. Ind. Appl. Math. 39, (2022).
  11. Ohnishi, M., Ishikawa, I., Kuroki, Y., and Ikeda, M., "Dynamic Structure Estimation from Bandit Feedback.", CoRR abs/2206.00861, (2022).
  12. Machida, T., Nagai, Y., and Hanaguri, T., "Zeeman effects on Yu-Shiba-Rusinov states", Phys. Rev. Research 4(3), 033182-1–033182-12, (2022).
  13. Kumagai, W., Sannai, A., and Kawano, M., "Universal approximation with neural networks on function spaces", J. Exp. Theor. Artif. Intell., (2022).
  14. KIRAL, E. M., KUAN, C. C., and LESESVRE, D., "Subconvexity For Twisted GL3 L-functions", Acta Arith., 281–302, (2022).
  15. Ishikawa, I., Teshima, T., Tojo, K., Oono, K., Ikeda, M., and Sugiyama, M., "Universal approximation property of invertible neural networks.", CoRR abs/2204.07415, (2022).
  16. Ikeda, M., Tu, Z., and Wakasa, K., "Small data blow-up of semi-linear wave equation with scattering dissipation and time-dependent mass", Evol. Equ. Control Theory 11(2), 515, (2022).
  17. Ikeda, M., Tu, Z., and Wakasa, K., "SMALL DATA BLOW-UP OF SEMI-LINEAR WAVE EQUATION WITH SCATTERING DISSIPATION AND TIME-DEPENDENT MASS", Evol. Equ. Control Theory 11(2), 515–536, (2022).
  18. Ikeda, M., Miyauchi, A., Takai, Y., and Yoshida, Y., "Finding Cheeger cuts in hypergraphs via heat equation", Theoret. Comput. Sci. 930, 1–23, (2022).
  19. Ikeda, M., Ishikawa, I., and Schlosser, C., "Koopman and Perron-Frobenius operators on reproducing kernel Banach spaces", Chaos 32(12), (2022).
  20. Ikeda, M., Ishikawa, I., and Sawano, Y., "Boundedness of composition operators on reproducing kernel Hilbert spaces with analytic positive definite functions", J. Math. Anal. Appl. 511(1), (2022).
  21. Hatano, N., Ikeda, M., Ishikawa, I., and Sawano, Y., "UNIVERSALITY OF NEURAL NETWORKS WITH A SIGMOIDAL ACTIVATION OR DISCRIMINATORY FUNCTIONS ON FUNCTIONAL BANACH LATTICES OVER THE REAL LINE", Journal of Mathematical Sciences 266(2), 342–352, (2022).
  22. Hatano, N., Ikeda, M., Ishikawa, I., and Sawano, Y., "Heaviside function as an activation function", J. Appl. Anal. 0(0), (2022).
  23. Hashimoto, Y., Ikeda, M., and Kadri, H., "Learning in RKHM: a C*-Algebraic Twist for Kernel Machines.", CoRR abs/2210.11855, (2022).
  24. Hamano, M., and Ikeda, M., "Equivalence of conditions on initial data below the ground state to NLS with a repulsive inverse power potential", J. Math. Phys. 63(3), (2022).
  25. Fukuda, I., and Ikeda, M., "Large time behavior of solutions to the Cauchy problem for the BBM-Burgers equation", J. Differential Equations 336, 275–314, (2022).
  26. Fukaya, N., Georgiev, V., and Ikeda, M., "On stability and instability of standing waves for 2d-nonlinear Schrödinger equations with point interaction", J. Differential Equations 321, 258–295, (2022).
  27. Fukaya, N., Georgiev, V., and Ikeda, M., "

    On stability and instability of standing waves for 2d-nonlinear Schrodinger equations with point interaction

    ", J. Differential Equations 321, 258–295, (2022).
  28. Chikami, N., Ikeda, M., and Taniguchi, K., "Optimal well-posedness and forward self-similar solution for the Hardy–Hénon parabolic equation in critical weighted Lebesgue spaces", Nonlinear Analysis 222, 112931, (2022).
  29. Chikami, N., Ikeda, M., and Taniguchi, K., "

    Optimal well-posedness and forward self-similar solution for the Hardy-H?non parabolic equation in critical weighted Lebesgue spaces

    ", Nonlinear Anal. Theory Methods Appl. 222, (2022).
  30. Bannai, K., Hagihara, K., Yamada, K., and Yamaoto, S., "p-adic polylogarithms and p-adic Hecke L-functions for totally real fields", Journal für die reine und angewandte Mathematik 791, 53–87, (2022).
  31. Xu, R., "A Numerical Method to Find the Optimal Thermodynamic Cycle in Microscopic Heat Engine", J. Stat. Phys. 184(3), (2021).
  32. Sonoda, S., Ishikawa, I., and Ikeda, M., "Ghosts in Neural Networks: Existence, Structure and Role of Infinite-Dimensional Null Space.", CoRR abs/2106.04770, (2021).
  33. Ohnishi, M., Notomista, G., Sugiyama, M., and Egerstedt, M., "Constraint learning for control tasks with limited duration barrier functions", Automatica 127, (2021).
  34. Ohnishi, M., Ishikawa, I., Lowrey, K., Ikeda, M., Kakade, S. M., and Kawahara, Y., "Koopman Spectrum Nonlinear Regulator and Provably Efficient Online Learning.", CoRR abs/2106.15775, (2021).
  35. Ikeda, M., and Sobajima, M., "Life-span of Blowup Solutions to Semilinear Wave Equation with Space-dependent Critical Damping", Funkcialaj Ekvacioj-serio Internacia 64(2), 137–162, (2021).
  36. Ikeda, M., Lin, J., and Tu, Z., "Small data blow-up for the weakly coupled system of the generalized Tricomi equations with multiple propagation speeds", J. Evol. Equ. 21(4), 3765–3796, (2021).
  37. Ikeda, M., "Global dynamics below the ground state for the focusing semilinear Schrödinger equation with a linear potential", J. Math. Anal. Appl. 503(1), 125291, (2021).
  38. Hirayama, H., Ikeda, M., and Tanaka, T., "Well-posedness for the fourth-order Schrödinger equation with third order derivative nonlinearities", Nonlinear Differential Equations and Applications NoDEA 28(5), 46, (2021).
  39. Hirayama, H., Ikeda, M., and Tanaka, T., "Well-posedness for the fourth-order Schrodinger equation with third order derivative nonlinearities", Nodea-nonlinear Differential Equations and Applications 28(5), (2021).
  40. Hatano, N., Ikeda, M., Ishikawa, I., and Sawano, Y., "Boundedness of composition operators on Morrey spaces and weak Morrey spaces", J. Inequal. Appl. 2021(1), (2021).
  41. Hatano, N., Ikeda, M., Ishikawa, I., and Sawano, Y., "A Global Universality of Two-Layer Neural Networks with ReLU Activations", J. Funct. Spaces 2021, (2021).
  42. Hashimoto, Y., Ishikawa, I., Ikeda, M., Komura, F., Katsura, T., and Kawahara, Y., "Reproducing kernel Hilbert C*-module and kernel mean embeddings.", J. Mach. Learn. Res. 22, 267:1–267:56, (2021).
  43. Hashimoto, Y., Ishikawa, I., Ikeda, M., Komura, F., Katsura, T., and Kawahara, Y., "Reproducing Kernel Hilbert C*-Modules and Kernel Mean Embeddings", J. Mach. Learn. Res. 22, 1–56, (2021).
国際会議 / Proceedings
  1. Sonoda, S., Ishi, H., Ishikawa, I., and Ikeda, M., "Joint Group Invariant Functions on Data-Parameter Domain Induce Universal Neural Networks", Proceedings on Symmetry and Geometry in Neural Representations, (2024).
  2. Sonoda, S., Hashimoto, Y., Ishikawa, I., and Ikeda, M., "Deep Ridgelet Transform: Voice with Koopman Operator Proves Universality of Formal Deep Networks", Proceedings on Symmetry and Geometry in Neural Representations, (2024).
  3. Tojo, K., and Yoshino, T., "A q-Analogue of the Family of Poincaré Distributions on the Upper Half Plane", Lecture Notes in Comput. Sci. 14071, (2023).
  4. Sonoda, S., Ishikawa, I., and Ikeda, M., "Universality of Group Convolutional Neural Networks Based on Ridgelet Analysis on Groups", Advances in Neural Information Processing Systems 35, 38680–38694, (2022).
  5. Sonoda, S., Ishikawa, I., and Ikeda, M., "Fully-Connected Network on Noncompact Symmetric Space and Ridgelet Transform based on Helgason-Fourier Analysis.", Icml, 20405–20422, (2022).
  6. Tojo, K., and Yoshino, T., "An Exponential Family on the Upper Half Plane and Its Conjugate Prior", Springer Proc. Math. Stat. 361, (2021).
  7. Takai, Y., Sannai, A., and Cordonnier, M., "On the number of linear functions composing deep neural network: Towards a refined definition of neural networks complexity.", Aistats, 3799–3807, (2021).
  8. Sonoda, S., Ishikawa, I., and Ikeda, M., "Ridge Regression with Over-parametrized Two-Layer Networks Converge to Ridgelet Spectrum.", Aistats, 2674–2682, (2021).
  9. Sannai, A., Imaizumi, M., and Kawano, M., "Improved generalization bounds of group invariant / equivariant deep networks via quotient feature spaces.", Uai, 771–780, (2021).