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Kengo Nakai

Machine-learning inference of fluid variables from data using reservoir computing
2018 · Kengo Nakai, Yoshitaka Saiki · Physical review. E · 80
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Dynamical system analysis of a data-driven model constructed by reservoir computing
2021 · Miki U. Kobayashi, Kengo Nakai, et al. · Physical review. E · 24
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Machine-learning construction of a model for a macroscopic fluid variable using the delay-coordinate of a scalar observable
2020 · Kengo Nakai, Yoshitaka Saiki · Discrete and Continuous Dynamical Systems - S · 12
Direction of Vorticity and a Refined Regularity Criterion for the Navier–Stokes Equations with Fractional Laplacian
2019 · Kengo Nakai · Journal of Mathematical Fluid Mechanics · 9
Long-term prediction of El Niño-Southern Oscillation using reservoir computing with data-driven realtime filter
2025 · Takuya Jinno, Takahito Mitsui, et al. · Chaos An Interdisciplinary Journal of Nonlinear Science · 4
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Constructing differential equations using only a scalar time-series about continuous time chaotic dynamics
2022 · Natsuki Tsutsumi, Kengo Nakai, et al. · Chaos An Interdisciplinary Journal of Nonlinear Science · 3
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Lyapunov analysis of data-driven models of high dimensional dynamics using reservoir computing: Lorenz-96 system and fluid flow
2024 · Miki U Kobayashi, Kengo Nakai, et al. · Journal of Physics Complexity · 2
Data-driven modeling from biased small training data using periodic orbits
2024 · Nakai, Kengo, Saiki, Yoshitaka · arXiv (Cornell University) · 1
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Constructing low-dimensional ordinary differential equations from chaotic time series of high- or infinite-dimensional systems using radial-function-based regression
2023 · Natsuki Tsutsumi, Kengo Nakai, et al. · Physical review. E · 1
Machine-learning prediction of fluid variables from data using reservoir computing
2018 · Kengo Nakai, Yoshitaka Saiki · arXiv (Cornell University) · 1
On the attractor in high-dimensional neural network dynamics of reservoir computing: A Lyapunov analysis viewpoint
2026 · Miki U. Kobayashi, Kengo Nakai, et al. · Chaos An Interdisciplinary Journal of Nonlinear Science
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Geometric structure of ideal data-driven dynamical model using RfR method
2026 · Tsutsumi, Natsuki, Nakai, Kengo, et al. · arXiv (Cornell University)
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Machine learning prediction of the Madden–Julian oscillation using reservoir computing
2026 · Tamaki Suematsu, Kengo Nakai, et al. · Japan Journal of Industrial and Applied Mathematics
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ManzaiSet: A Multimodal Dataset of Viewer Responses to Japanese Manzai Comedy
2025 · Kawamura, Kazuki, Nakai, Kengo, et al. · arXiv (Cornell University)
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Data-driven ordinary-differential-equation modeling of high-frequency complex dynamics via a low-frequency dynamics model
2025 · Natsuki Tsutsumi, Kengo Nakai, et al. · Physical review. E
Constructing low-dimensional ordinary differential equations from chaotic time series of high/infinite-dimensional systems using radial function-based regression
2023 · Tsutsumi, Natsuki, Nakai, Kengo, et al. · arXiv (Cornell University)
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Wkb近似の適用可能範囲に対する数値的考察
2020 · Nakai, Kengo · Institutional Repositories DataBase (IRDB)
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流体方程式の機械学習によるモデリングと解の正則性の判定条件
2020 · Nakai, Kengo · Institutional Repositories DataBase (IRDB)
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DIRECTION OF VORTICITY AND A REFINED BLOW-UP CRITERION FOR THE NAVIER-STOKES EQUATIONS WITH FRACTIONAL LAPLACIAN (Mathematical Analysis in Fluid and Gas Dynamics)
2018 · Kengo Nakai · Institutional Repositories DataBase (IRDB)
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Soliton regions determined by initial values in the K-dV equation
1979 · Shoichi Kawamoto, Masao Kido, et al.
Works count: 20
Citation count: 137
H-index: 4
I10-index: 3
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