Neural network approach to the study of dynamics and structure of molecular systems

被引:0
|
作者
Getino, Coral [1 ]
Sumpter, Bobby G. [1 ]
Noid, Donald W. [1 ]
机构
[1] Oak Ridge Natl Lab, Oak Ridge, United States
关键词
10;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
页码:849 / 855
相关论文
共 50 条
  • [31] A neural network approach to the analysis of city systems
    Kropp, J
    APPLIED GEOGRAPHY, 1998, 18 (01) : 83 - 96
  • [32] Neural network approach for identification of Hammerstein systems
    Janczak, A
    INTERNATIONAL JOURNAL OF CONTROL, 2003, 76 (17) : 1749 - 1766
  • [33] A neural network approach to crystal structure classification
    Shetty, KR
    Rao, A
    Gopala, K
    CURRENT SCIENCE, 1999, 76 (05): : 670 - 676
  • [34] Structural transitions in liquid semiconductor alloys: A molecular dynamics study with a neural network potential
    Fang, Yi-Bin
    Shang, Cheng
    Liu, Zhi-Pan
    Gong, Xin-Gao
    JOURNAL OF CHEMICAL PHYSICS, 2024, 161 (10):
  • [35] Neural network enabled molecular dynamics study of HfO2 phase transitions
    Bichelmaier, Sebastian
    Carrete, Jesus
    Madsen, Georg K. H.
    PHYSICAL REVIEW B, 2024, 110 (17)
  • [36] Penalty function approach to recurrent neural network dynamics
    Milotti, E
    PHYSICAL REVIEW E, 1997, 56 (01): : 1266 - 1269
  • [37] A neural network based approach for measurement dynamics compensation
    Georgieva, P
    de Azevedo, SF
    APPLIED ARTIFICIAL INTELLIGENCE, 2002, 16 (06) : 423 - 442
  • [38] Structure and dynamics of water -: molecular dynamics study
    Sokól, M
    Dawid, A
    Dendzik, Z
    Gburski, Z
    JOURNAL OF MOLECULAR STRUCTURE, 2004, 704 (1-3) : 341 - 345
  • [39] Nonlinear, Nonequilibrium Landscape Approach to Neural Network Dynamics
    Wedemann, Roseli S.
    Plastino, Angel R.
    ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING, ICANN 2020, PT II, 2020, 12397 : 180 - 191
  • [40] Leveraging the Graph Structure of Neural Network Training Dynamics
    Vahedian, Fatemeh
    Li, Ruiyu
    Trivedi, Puja
    Jin, Di
    Koutra, Danai
    PROCEEDINGS OF THE 31ST ACM INTERNATIONAL CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT, CIKM 2022, 2022, : 4545 - 4549