Importance of data selection for machine learning-based atomistic potentials

被引：0
|
作者：
Smith, Justin [1 ]
Nebgen, Benjamin [3 ]
Lubbers, NIcholas [2 ]
Tretiak, Sergei [4 ]
Barros, Kipton [3 ]
机构：
[1] Los Alamos Natl Lab, T 1 CNLS, Los Alamos, NM USA
[2] Los Alamos Natl Lab, CCS 3, Los Alamos, NM USA
[3] Los Alamos Natl Lab, Los Alamos, NM USA
[4] Los Alamos Natl Lab, Theoret Div, T 1 CINT, MS B268, Los Alamos, NM USA
来源：
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY | 2019年 / 258卷
关键词：
D O I：
暂无
中图分类号：
O6 [化学];
学科分类号：
0703 ;
摘要：
433-COMP
引用
收藏
页数：1
相关论文
共 50 条
  • [1] Machine Learning-Based Feature Extraction and Selection
    Ruano-Ordas, David
    APPLIED SCIENCES-BASEL, 2024, 14 (15):
  • [2] Roadmap for the development of machine learning-based interatomic potentials
    Zhang, Yong-Wei
    Sorkin, Viacheslav
    Aitken, Zachary H.
    Politano, Antonio
    Behler, Joerg
    Thompson, Aidan
    Ko, Tsz Wai
    Ong, Shyue Ping
    Chalykh, Olga
    Korogod, Dmitry
    Podryabinkin, Evgeny
    Shapeev, Alexander
    Li, Ju
    Mishin, Yuri
    Pei, Zongrui
    Liu, Xianglin
    Kim, Jaesun
    Park, Yutack
    Hwang, Seungwoo
    Han, Seungwu
    Sheriff, Killian
    Cao, Yifan
    Freitas, Rodrigo
    MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING, 2025, 33 (02)
  • [3] Pitfalls of Machine Learning-Based Personnel Selection Fairness, Transparency, and Data Quality
    Goretzko, David
    Finja Israel, Laura Sophia
    JOURNAL OF PERSONNEL PSYCHOLOGY, 2022, 21 (01) : 37 - 47
  • [4] Data Processing and Model Selection for Machine Learning-based Network Intrusion Detection
    Sahu, Abhijeet
    Mao, Zeyu
    Davis, Katherine
    Goulart, Ana E.
    2020 IEEE INTERNATIONAL WORKSHOP TECHNICAL COMMITTEE ON COMMUNICATIONS QUALITY AND RELIABILITY (CQR), 2020, : 49 - 54
  • [5] Perspective: Machine learning potentials for atomistic simulations
    Behler, Joerg
    JOURNAL OF CHEMICAL PHYSICS, 2016, 145 (17):
  • [6] Introduction to machine learning potentials for atomistic simulations
    Thiemann, Fabian L.
    O'Neill, Niamh
    Kapil, Venkat
    Michaelides, Angelos
    Schran, Christoph
    JOURNAL OF PHYSICS-CONDENSED MATTER, 2025, 37 (07)
  • [7] A universal strategy for the creation of machine learning-based atomistic force fields
    Tran Doan Huan
    Rohit Batra
    James Chapman
    Sridevi Krishnan
    Lihua Chen
    Rampi Ramprasad
    npj Computational Materials, 3
  • [8] A universal strategy for the creation of machine learning-based atomistic force fields
    Huan, Tran Doan
    Batra, Rohit
    Chapman, James
    Krishnan, Sridevi
    Chen, Lihua
    Ramprasad, Rampi
    NPJ COMPUTATIONAL MATERIALS, 2017, 3
  • [9] A Machine Learning-Based Wrapper Method for Feature Selection
    Patel, Damodar
    Saxena, Amit
    Wang, John
    INTERNATIONAL JOURNAL OF DATA WAREHOUSING AND MINING, 2024, 20 (01)
  • [10] Machine Learning-Based Antenna Selection in Wireless Communications
    Joung, Jingon
    IEEE COMMUNICATIONS LETTERS, 2016, 20 (11) : 2241 - 2244
12345