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RESEARCH PAPER · The Journal of Physical Chemistry A · 2020

Symmetrical Graph Neural Network for Quantum Chemistry with Dual Real and Momenta Space

Shuqian Ye, Jiechun Liang, Rulin Liu, Xi Zhu

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42 direct citing works

Symmetrical Graph Neural Network for Quantum Chemistry with Dual Real and Momenta SpaceOriginalEnabling Nonlinear Manifold Projection Reduced-Order Models by Extending Convolutional Neural Networks to Unstructured Data.5Unsupervised Machine Learning Discovery of Chemical and Physical Transformation Pathways from Imaging Data2QM-symex, update of the QM-sym database with excited state information for 173 kilo molecules30A review on machine learning approaches and trends in drug discovery472Catalyst deep neural networks (Cat-DNNs) in singlet fission property prediction5Machine-learning-assisted low dielectric constant polymer discovery49Learning Connectivity with Graph Convolutional Networks19Essentiality of the Basis Function in Deep Learning Physical Chemistry Properties0Geometric Feature Extraction of Point Cloud of Chemical Reactor Based on Dynamic Graph Convolution Neural Network5Machine Learning-Assisted Discovery of High-Voltage Organic Materials for Rechargeable Batteries37Coal Wall and Roof Segmentation in the Coal Mine Working Face Based on Dynamic Graph Convolution Neural Networks8The emerging graph neural networks for intelligent fault diagnostics and prognostics: A guideline and a benchmark study673Embedding physics into deep learning for modeling spatiotemporal systems1Potential Application of Machine-Learning-Based Quantum Chemical Methods in Environmental Chemistry59CrysXPP: An explainable property predictor for crystalline materials24Machine Learning in Computational Chemistry1Hyperscale FPGA-as-a-service architecture for large-scale distributed graph neural network29Machine learning, artificial intelligence, and chemistry: How smart algorithms are reshaping simulation and the laboratory35Analyzing point cloud of coal mining process in much dust environment based on dynamic graph convolution neural network21SCGraph: Accelerating Sample-based GNN Training by Staged Caching of Features on GPUs1Physical pooling functions in graph neural networks for molecular property prediction52Characterizing the Scalability of Graph Convolutional Networks on Intel ® PIUMA6Unsupervised machine learning discovery of structural units and transformation pathways from imaging data8Machine learning approaches for screening of materials in flexible electronic devices0Graph representation of multi-dimensional materials2An exponential smoothing multi-head graph attention network (ESMGAT) method for damage zone localization on wind turbine blades9A Fairness Group Recommendation Algorithm Based On User Activity9Comparison of Machine Learning Approaches for Prediction of the Equivalent Alkane Carbon Number for Microemulsions Based on Molecular Properties4Graph-based learning and optimization0Spectral-Aware Augmentation for Enhanced Graph Representation Learning3Graph pooling for graph-level representation learning: a survey45State‐Of‐The‐Art Structural Regulation Methods and Quantum Chemistry for Carbon‐Based Single‐Atom Catalysts in Advanced Oxidation Process: Critical Perspectives into Molecular Level40Towards sustainable exploration of chemical spaces with machine learning0

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33 direct citing papers saved.

  1. Enabling Nonlinear Manifold Projection Reduced-Order Models by Extending Convolutional Neural Networks to Unstructured Data.

    OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2020-06-11

    John T. Tencer, Kevin Potter

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  2. Unsupervised Machine Learning Discovery of Chemical and Physical Transformation Pathways from Imaging Data

    arXiv (Cornell University) · 2020-10-19

    Sergei V. Kalinin, Ondrej Dyck, Ayana Ghosh, Yongtao Liu, Roger B. Proksch, Bobby G. Sumpter, Maxim A Ziatdinov

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  3. QM-symex, update of the QM-sym database with excited state information for 173 kilo molecules

    Scientific Data · 2020-11-18

    Jiechun Liang, Shuqian Ye, Tianshu Dai, Ziyue Zha, Yuechen Gao, Xi Zhu

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  4. A review on machine learning approaches and trends in drug discovery

    Computational and Structural Biotechnology Journal · 2021-01-01

    Paula Carracedo-Reboredo, José Liñares-Blanco, Nereida Rodríguez-Fernández, Francisco Cedrón, Francisco Javier Novoa, Adrián Carballal, Víctor Maojo, Alejandro Pazos, Carlos Fernandez-Lozano

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  5. Catalyst deep neural networks (Cat-DNNs) in singlet fission property prediction

    Physical Chemistry Chemical Physics · 2021-01-01

    Shuqian Ye, Jiechun Liang, Xi Zhu

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  6. Machine-learning-assisted low dielectric constant polymer discovery

    Materials Chemistry Frontiers · 2021-01-01

    Jiechun Liang, Shangqian Xu, Linfeng Hu, Yu Zhao, Xi Zhu

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  7. Learning Connectivity with Graph Convolutional Networks

    Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · 2021-01-10

    Hichem Sahbi

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  8. Essentiality of the Basis Function in Deep Learning Physical Chemistry Properties

    The Journal of Physical Chemistry Letters · 2021-07-06

    Rulin Liu, Xi Zhu

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  9. Geometric Feature Extraction of Point Cloud of Chemical Reactor Based on Dynamic Graph Convolution Neural Network

    ACS Omega · 2021-08-12

    Zhizhong Xing, Shuanfeng Zhao, Wei Guo, Xiaojun Guo

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  10. Machine Learning-Assisted Discovery of High-Voltage Organic Materials for Rechargeable Batteries

    The Journal of Physical Chemistry C · 2021-09-28

    Shangqian Xu, Jiechun Liang, Yunduo Yu, Rulin Liu, Yao Xu, Xi Zhu, Yu Zhao

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  11. Coal Wall and Roof Segmentation in the Coal Mine Working Face Based on Dynamic Graph Convolution Neural Networks

    ACS Omega · 2021-11-15

    Zhizhong Xing, Shuanfeng Zhao, Wei Guo, Xiaojun Guo, Shenquan Wang, Junjie Ma, Haitao He

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  12. The emerging graph neural networks for intelligent fault diagnostics and prognostics: A guideline and a benchmark study

    Mechanical Systems and Signal Processing · 2021-12-01

    Tianfu Li, Zheng Zhou, Sinan Li, Chuang Sun, Ruqiang Yan, Xuefeng Chen

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  13. Embedding physics into deep learning for modeling spatiotemporal systems

    Unknown journal · 2022-01-01

    Pu Ren

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  14. Potential Application of Machine-Learning-Based Quantum Chemical Methods in Environmental Chemistry

    Environmental Science & Technology · 2022-01-27

    Deming Xia, Jingwen Chen, Zhiqiang Fu, Tong Xu, Zhongyu Wang, Wenjia Liu, Hong‐Bin Xie, Willie J.G.M. Peijnenburg

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  15. CrysXPP: An explainable property predictor for crystalline materials

    npj Computational Materials · 2022-03-18

    Kishalay Das, Bidisha Samanta, Pawan Goyal, Seung‐Cheol Lee, Satadeep Bhattacharjee, Niloy Ganguly

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  16. Machine Learning in Computational Chemistry

    Unknown journal · 2022-05-01

    David Kuntz

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  17. Hyperscale FPGA-as-a-service architecture for large-scale distributed graph neural network

    Proceedings - International Symposium on Computer Architecture/Proceedings · 2022-05-31

    Shuangchen Li, Dimin Niu, Yuhao Wang, Wei Han, Zhe Zhang, Tianchan Guan, Yijin Guan, Heng Liu, Linyong Huang, Zhaoyang Du, Fei Xue, Yuanwei Fang, Hongzhong Zheng, Yuan Xie

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  18. Machine learning, artificial intelligence, and chemistry: How smart algorithms are reshaping simulation and the laboratory

    Pure and Applied Chemistry · 2022-08-01

    David Kuntz, Angela K. Wilson

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  19. Analyzing point cloud of coal mining process in much dust environment based on dynamic graph convolution neural network

    Environmental Science and Pollution Research · 2022-08-13

    Zhizhong Xing, Shuanfeng Zhao, Wei Guo, Xiaojun Guo, Shenquan Wang, Mingyue Li, Yuan Wang, Haitao He

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  20. SCGraph: Accelerating Sample-based GNN Training by Staged Caching of Features on GPUs

    IEEE International Conference on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom) · 2022-12-01

    Yuqi He, Zhiquan Lai, Zhejiang Ran, Lizhi Zhang, Dongsheng Li

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  21. Physical pooling functions in graph neural networks for molecular property prediction

    Computers & Chemical Engineering · 2023-02-24

    Artur M. Schweidtmann, Jan G. Rittig, Jana M. Weber, Martin Grohe, Manuel Dahmen, Kai O. Leonhard, Alexander Mitsos

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  22. Characterizing the Scalability of Graph Convolutional Networks on Intel ® PIUMA

    IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) · 2023-04-01

    Matthew Joseph Adiletta, Jesmin Jahan Tithi, Emmanouil Farsarakis, Gerasimos Gerogiannis, Robert Adolf, Robert Benke, Sidharth Kashyap, Samuel Hsia, Kartik Lakhotia, Fabrizio Petrini, Gu-Yeon Wei, David M. Brooks

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  23. Unsupervised machine learning discovery of structural units and transformation pathways from imaging data

    APL Machine Learning · 2023-06-01

    Sergei V. Kalinin, Ondrej Dyck, Ayana Ghosh, Yongtao Liu, Bobby G. Sumpter, Maxim A Ziatdinov

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  24. Machine learning approaches for screening of materials in flexible electronic devices

    Unknown journal · 2024-01-01

    Siyan Deng

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  25. Graph representation of multi-dimensional materials

    Journal of Physics Materials · 2024-04-01

    Carina T Cai, Amanda J. Parker, Amanda Susan Barnard

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  26. An exponential smoothing multi-head graph attention network (ESMGAT) method for damage zone localization on wind turbine blades

    Composite Structures · 2024-05-29

    Zhimin Zhao, Nian-Zhong Chen

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  27. A Fairness Group Recommendation Algorithm Based On User Activity

    International Journal of Computational Intelligence Systems · 2024-08-05

    Junjie Jia, Fen Wang, Huijuan Wang, Shilong Liu

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  28. Comparison of Machine Learning Approaches for Prediction of the Equivalent Alkane Carbon Number for Microemulsions Based on Molecular Properties

    The Journal of Physical Chemistry A · 2024-08-06

    Nicholas Furth, Adam E. Imel, Thomas A. Zawodzinski

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  29. Graph-based learning and optimization

    Unknown journal · 2024-10-17

    Taha Halal

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  30. Spectral-Aware Augmentation for Enhanced Graph Representation Learning

    ACM International Conference on Information and Knowledge Management (CIKM) · 2024-10-20

    Kaiqi Yang, Haoyu Han, Wei Jin, Hui Liu

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  31. Graph pooling for graph-level representation learning: a survey

    Artificial Intelligence Review · 2024-12-20

    Zhipeng Li, Siguo Wang, Qinhu Zhang, Yijie Pan, Naian Xiao, Jia-Yang Guo, Changan Yuan, Wenjian Liu, De-Shuang Huang

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  32. State‐Of‐The‐Art Structural Regulation Methods and Quantum Chemistry for Carbon‐Based Single‐Atom Catalysts in Advanced Oxidation Process: Critical Perspectives into Molecular Level

    Advanced Materials · 2025-05-22

    Huayue Kang, Yaoning Chen, Min Cheng, Huiqin Guo, Gaoxia Zhang, Qingkai Shi, Wencheng Zhou, Chen Zhao, Bin Zou, Xinyue Lv, Ziyue Yuan, Guangming Zeng

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  33. Towards sustainable exploration of chemical spaces with machine learning

    Digital Discovery · 2026-01-01

    Leonardo Rafael Medrano Sandonas, David Balcells, Tom Barnowsky, Anton S. Bochkarev, Jacqueline Cole, Volker L. Deringer, Werner Dobrautz, Adrian Ehrenhofer, Thorben Frank, Pascal Friederich, Rico Friedrich, Janine George, Luca M. Ghiringhelli, Alejandra Hinostroza Caldas, Veronika Jurásková, Hannes Kneiding, Yury Lysogorskiy, Johannes T. Margraf, Hanna Türk, O. Anatole von Lilienfield, Milica Todorović, Alexandre Tkatchenko, Mariana Rossi, Gianaurelio Cuniberti

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