Images of chemical structures as molecular representations for deep learning

被引：0
|
作者：
Matthew R. Wilkinson
Uriel Martinez-Hernandez
Chick C. Wilson
Bernardo Castro-Dominguez
机构：
[1] University of Bath,Department of Chemical Engineering
[2] University of Bath,EPSRC Centre for Innovative Manufacturing in Continuous Manufacturing and Crystallisation (CMAC)
[3] University of Bath,Centre of Sustainable and Circular Technologies (CSCT)
[4] University of Bath,Centre for Autonomous Robotics (CENTAUR)
[5] University of Bath,Department of Chemistry
来源：
Journal of Materials Research | 2022年 / 37卷
关键词：
Molecular representation; Deep learning; Artificial Intelligence; Pharmaceutical; Images; Industry 4.0;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：2293 / 2303
页数：10
相关论文
共 50 条
  • [1] Images of chemical structures as molecular representations for deep learning
    Wilkinson, Matthew R.
    Martinez-Hernandez, Uriel
    Wilson, Chick C.
    Castro-Dominguez, Bernardo
    [J]. JOURNAL OF MATERIALS RESEARCH, 2022, 37 (14) : 2293 - 2303
  • [2] Geometric deep learning on molecular representations
    Kenneth Atz
    Francesca Grisoni
    Gisbert Schneider
    [J]. Nature Machine Intelligence, 2021, 3 : 1023 - 1032
  • [3] Geometric deep learning on molecular representations
    Atz, Kenneth
    Grisoni, Francesca
    Schneider, Gisbert
    [J]. NATURE MACHINE INTELLIGENCE, 2021, 3 (12) : 1023 - 1032
  • [4] Pretraining deep learning molecular representations for property prediction
    Liu, Bowen
    Hu, Weihua
    Leskovec, Jure
    Liang, Percy
    Pande, Vijay
    [J]. ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2019, 258
  • [5] Deep learning efficient representations of chemical concepts and quantum chemistry
    Matlock, Matthew
    Dang, Ne
    Swamidass, S. Joshua
    [J]. ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2018, 256
  • [6] Unsupervised Learning of Human Action Categories in Still Images with Deep Representations
    Zheng, Yunpeng
    Li, Xuelong
    Lu, Xiaoqiang
    [J]. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2019, 15 (04)
  • [7] PROBABILISTIC DEEP LEARNING FOR VALIDATION OF EMERGENT STRUCTURES IN SIMULATED IMAGES
    Kaiser, Bryan
    Hickmann, Kyle
    [J]. PROCEEDINGS OF ASME 2023 VERIFICATION, VALIDATION, AND UNCERTAINTY QUANTIFICATION SYMPOSIUM, VVUQ2023, 2023,
  • [8] Binary segmentation of medical images using implicit spline representations and deep learning
    Barrowclough, Oliver J. D.
    Muntingh, Georg
    Nainamalai, Varatharajan
    Stangeby, Ivar
    [J]. COMPUTER AIDED GEOMETRIC DESIGN, 2021, 85
  • [9] Exploring Deep Learning for Metalloporphyrins: Databases, Molecular Representations, and Model Architectures
    Su, An
    Zhang, Chengwei
    She, Yuan-Bin
    Yang, Yun-Fang
    [J]. CATALYSTS, 2022, 12 (11)
  • [10] A Deep Learning Approach for Molecular Classification Based on AFM Images
    Carracedo-Cosme, Jaime
    Romero-Muniz, Carlos
    Perez, Ruben
    [J]. NANOMATERIALS, 2021, 11 (07)
12345