Author Correction: Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning

被引:0
|
作者
Dipendra Jha
Kamal Choudhary
Francesca Tavazza
Wei-keng Liao
Alok Choudhary
Carelyn Campbell
Ankit Agrawal
机构
[1] Northwestern University,Department of Electrical and Computer Engineering
[2] National Institute of Standards and Technology,Thermodynamics and Kinetics Group
来源
Nature Communications | / 11卷
关键词
D O I
暂无
中图分类号
学科分类号
摘要
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
引用
收藏
相关论文
共 50 条
  • [1] Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning
    Jha, Dipendra
    Choudhary, Kamal
    Tavazza, Francesca
    Liao, Wei-keng
    Choudhary, Alok
    Campbell, Carelyn
    Agrawal, Ankit
    NATURE COMMUNICATIONS, 2019, 10 (1)
  • [2] Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning
    Dipendra Jha
    Kamal Choudhary
    Francesca Tavazza
    Wei-keng Liao
    Alok Choudhary
    Carelyn Campbell
    Ankit Agrawal
    Nature Communications, 10
  • [3] Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning (vol 10, 5316, 2019)
    Jha, Dipendra
    Choudhary, Kamal
    Tavazza, Francesca
    Liao, Wei-keng
    Choudhary, Alok
    Campbell, Carelyn
    Agrawal, Ankit
    NATURE COMMUNICATIONS, 2020, 11 (01)
  • [4] Leveraging Remote Sensing Data for Yield Prediction with Deep Transfer Learning
    Huber, Florian
    Inderka, Alvin
    Steinhage, Volker
    SENSORS, 2024, 24 (03)
  • [5] Leveraging transfer learning with deep learning for crime prediction
    Butt, Umair Muneer
    Letchmunan, Sukumar
    Hassan, Fadratul Hafinaz
    Koh, Tieng Wei
    PLOS ONE, 2024, 19 (04):
  • [6] Improving Material Property Prediction by Leveraging the Large-Scale Computational Database and Deep Learning
    Chen, Pin
    Chen, Jianwen
    Yan, Hui
    Mo, Qing
    Xu, Zexin
    Liu, Jinyu
    Zhang, Wenqing
    Yang, Yuedong
    Lu, Yutong
    JOURNAL OF PHYSICAL CHEMISTRY C, 2022, 126 (38): : 16297 - 16305
  • [7] Computational Screening of New Perovskite Materials Using Transfer Learning and Deep Learning
    Li, Xiang
    Dan, Yabo
    Dong, Rongzhi
    Cao, Zhuo
    Niu, Chengcheng
    Song, Yuqi
    Li, Shaobo
    Hu, Jianjun
    APPLIED SCIENCES-BASEL, 2019, 9 (24):
  • [8] Author Correction: Enhancing protein backbone angle prediction by using simpler models of deep neural networks
    Fereshteh Mataeimoghadam
    M. A. Hakim Newton
    Abdollah Dehzangi
    Abdul Karim
    B. Jayaram
    Shoba Ranganathan
    Abdul Sattar
    Scientific Reports, 11
  • [9] QRChEM: A Deep Learning Framework for Materials Property Prediction and Design Using QR Codes
    Uthayakumar, Haripriyan
    Krishna, K. Rahul
    Jain, Raj
    Kumar, Rajnish
    Patra, Tarak K.
    ACS ENGINEERING AU, 2023, 4 (01): : 91 - 98
  • [10] Materials representation and transfer learning for multi-property prediction
    Kong, Shufeng
    Guevarra, Dan
    Gomes, Carla P.
    Gregoire, John M.
    APPLIED PHYSICS REVIEWS, 2021, 8 (02)