These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

113 related articles for article (PubMed ID: 37073016)

  • 61. Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control.
    Brunton SL; Brunton BW; Proctor JL; Kutz JN
    PLoS One; 2016; 11(2):e0150171. PubMed ID: 26919740
    [TBL] [Abstract][Full Text] [Related]  

  • 62. Model selection of chaotic systems from data with hidden variables using sparse data assimilation.
    Ribera H; Shirman S; Nguyen AV; Mangan NM
    Chaos; 2022 Jun; 32(6):063101. PubMed ID: 35778121
    [TBL] [Abstract][Full Text] [Related]  

  • 63. Knowledge-based learning of nonlinear dynamics and chaos.
    Jiahao TZ; Hsieh MA; Forgoston E
    Chaos; 2021 Nov; 31(11):111101. PubMed ID: 34881606
    [TBL] [Abstract][Full Text] [Related]  

  • 64. An in-depth numerical study of the two-dimensional Kuramoto-Sivashinsky equation.
    Kalogirou A; Keaveny EE; Papageorgiou DT
    Proc Math Phys Eng Sci; 2015 Jul; 471(2179):20140932. PubMed ID: 26345218
    [TBL] [Abstract][Full Text] [Related]  

  • 65. Characterization of chaotic dynamics in the human menstrual cycle.
    Derry G; Derry P
    Nonlinear Biomed Phys; 2010 Oct; 4(1):5. PubMed ID: 20923559
    [TBL] [Abstract][Full Text] [Related]  

  • 66. Initializing LSTM internal states via manifold learning.
    Kemeth FP; Bertalan T; Evangelou N; Cui T; Malani S; Kevrekidis IG
    Chaos; 2021 Sep; 31(9):093111. PubMed ID: 34598443
    [TBL] [Abstract][Full Text] [Related]  

  • 67. Deep learning for centre manifold reduction and stability analysis in nonlinear systems.
    Ghadami A; Epureanu BI
    Philos Trans A Math Phys Eng Sci; 2022 Aug; 380(2229):20210212. PubMed ID: 35719074
    [TBL] [Abstract][Full Text] [Related]  

  • 68. Reduction of dimension for nonlinear dynamical systems.
    Harrington HA; Van Gorder RA
    Nonlinear Dyn; 2017; 88(1):715-734. PubMed ID: 32226227
    [TBL] [Abstract][Full Text] [Related]  

  • 69. Interpolating Strange Attractors via Fractional Brownian Bridges.
    Raubitzek S; Neubauer T; Friedrich J; Rauber A
    Entropy (Basel); 2022 May; 24(5):. PubMed ID: 35626601
    [TBL] [Abstract][Full Text] [Related]  

  • 70. Nonuniform State Space Reconstruction for Multivariate Chaotic Time Series.
    Han M; Ren W; Xu M; Qiu T
    IEEE Trans Cybern; 2019 May; 49(5):1885-1895. PubMed ID: 29993852
    [TBL] [Abstract][Full Text] [Related]  

  • 71. Can the analytic techniques of nonlinear dynamics distinguish periodic, random and chaotic signals?
    Denton TA; Diamond GA
    Comput Biol Med; 1991; 21(4):243-63. PubMed ID: 1764933
    [TBL] [Abstract][Full Text] [Related]  

  • 72. Model-assisted deep learning of rare extreme events from partial observations.
    Asch A; J Brady E; Gallardo H; Hood J; Chu B; Farazmand M
    Chaos; 2022 Apr; 32(4):043112. PubMed ID: 35489849
    [TBL] [Abstract][Full Text] [Related]  

  • 73. Feedback control of chaotic systems using multiple shooting shadowing and application to Kuramoto-Sivashinsky equation.
    Shawki K; Papadakis G
    Proc Math Phys Eng Sci; 2020 Aug; 476(2240):20200322. PubMed ID: 32922158
    [TBL] [Abstract][Full Text] [Related]  

  • 74. Differential Geometry Methods for Constructing Manifold-Targeted Recurrent Neural Networks.
    Claudi F; Branco T
    Neural Comput; 2022 Jul; 34(8):1790-1811. PubMed ID: 35798324
    [TBL] [Abstract][Full Text] [Related]  

  • 75. A unified approach to attractor reconstruction.
    Pecora LM; Moniz L; Nichols J; Carroll TL
    Chaos; 2007 Mar; 17(1):013110. PubMed ID: 17411246
    [TBL] [Abstract][Full Text] [Related]  

  • 76. Dynamics of impurities in a three-dimensional volume-preserving map.
    Das S; Gupte N
    Phys Rev E Stat Nonlin Soft Matter Phys; 2014 Jul; 90(1):012906. PubMed ID: 25122359
    [TBL] [Abstract][Full Text] [Related]  

  • 77. Nonlinear dynamics of a dispersive anisotropic Kuramoto-Sivashinsky equation in two space dimensions.
    Tomlin RJ; Kalogirou A; Papageorgiou DT
    Proc Math Phys Eng Sci; 2018 Mar; 474(2211):20170687. PubMed ID: 29662339
    [TBL] [Abstract][Full Text] [Related]  

  • 78. Predicting chaos for infinite dimensional dynamical systems: the Kuramoto-Sivashinsky equation, a case study.
    Smyrlis YS; Papageorgiou DT
    Proc Natl Acad Sci U S A; 1991 Dec; 88(24):11129-32. PubMed ID: 11607246
    [TBL] [Abstract][Full Text] [Related]  

  • 79. Reservoir observers: Model-free inference of unmeasured variables in chaotic systems.
    Lu Z; Pathak J; Hunt B; Girvan M; Brockett R; Ott E
    Chaos; 2017 Apr; 27(4):041102. PubMed ID: 28456169
    [TBL] [Abstract][Full Text] [Related]  

  • 80. Hebbian learning of context in recurrent neural networks.
    Brunel N
    Neural Comput; 1996 Nov; 8(8):1677-710. PubMed ID: 8888613
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 6.