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31 ta ish

Ish: Structure to Property: Machine Learning Methods for Predicting Electronic Properties of Crystals

  1. Commentary: The Materials Project: A materials genome approach to accelerating materials innovation

    Anubhav Jain, Shyue Ping Ong, Geoffroy Hautier +8

    MaqolaOchiq kirish201314 iqtibos
    ABI

  2. Applications of machine learning in drug discovery and development

    Jessica Vamathevan, Dominic A. Clark, Paul Czodrowski +8

    Sharh maqola20197 iqtibos
    ABI

  3. Review on forecasting of photovoltaic power generation based on machine learning and metaheuristic techniques

    Muhammad Naveed Akhter, Saad Mekhilef, Hazlie Mokhlis +1

    Maqola20194 iqtibos
    ABI

  4. Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

    Chi Chen, Weike Ye, Yunxing Zuo +2

    Maqola20194 iqtibos
    ABI

  5. Machine Learning for Catalysis Informatics: Recent Applications and Prospects

    Takashi Toyao, Zen Maeno, Satoru Takakusagi +3

    Maqola20194 iqtibos
    ABI

  6. Predicting the state of charge and health of batteries using data-driven machine learning

    Man‐Fai Ng, Jin Zhao, Qingyu Yan +2

    Maqola20204 iqtibos
    ABI

  7. Machine learning for alloys

    Gus L. W. Hart, Tim Mueller, Cormac Toher +1

    Sharh maqola20214 iqtibos
    ABI

  8. On representing chemical environments

    Albert P. Bartók, Risi Kondor, Gábor Cśanyi

    Maqola20133 iqtibos
    ABI

  9. Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties

    Tian Xie, Jeffrey C. Grossman

    Maqola20183 iqtibos
    ABI

  10. Machine-learning guided discovery of a new thermoelectric material

    Yuma Iwasaki, Ichiro Takeuchi, Valentin Stanev +10

    Maqola20193 iqtibos
    ABI

  11. The rise of the X-ray atomic pair distribution function method: a series of fortunate events

    Simon J. L. Billinge

    Maqola20193 iqtibos
    ABI

  12. Machine learning assisted materials design and discovery for rechargeable batteries

    Yue Liu, Biru Guo, Xinxin Zou +2

    Maqola20203 iqtibos
    ABI

  13. Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures

    Shuo Zhang, Yang Liu, Lei Xie

    Preprint20203 iqtibos
    ABI

  14. Density of states prediction for materials discovery via contrastive learning from probabilistic embeddings

    Shufeng Kong, Francesco Ricci, Dan Guevarra +3

    Maqola20223 iqtibos
    ABI

  15. Unified representation of molecules and crystals for machine learning

    Haoyan Huo, Matthias Rupp

    Maqola20223 iqtibos
    ABI

  16. Machine learning techniques for prediction of capacitance and remaining useful life of supercapacitors: A comprehensive review

    Vaishali A. Sawant, Rashmi Deshmukh, Chetan J. Awati

    Sharh maqola20223 iqtibos
    ABI

  17. Sarlavhasiz

    Boshqa2 iqtibos
    ABI

  18. Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

    Aidan P. Thompson, Laura Swiler, Christian Robert Trott +2

    Maqola20142 iqtibos
    ABI

  19. Learning the electronic density of states in condensed matter

    Chiheb Ben Mahmoud, Andrea Anelli, Gábor Cśanyi +1

    Maqola20202 iqtibos
    ABI

  20. Direct Prediction of Phonon Density of States With Euclidean Neural Networks.

    Zhantao Chen, Nina Andrejevic, Tess Smidt +7

    Maqola20212 iqtibos
    ABI

  21. Machine learning potentials for extended systems: a perspective

    Jörg Behler, Gábor Cśanyi

    Maqola20212 iqtibos
    ABI

  22. Sarlavhasiz

    Boshqa2 iqtibos
    ABI

  23. Sarlavhasiz

    Boshqa2 iqtibos
    ABI

  24. Physically Informed Machine Learning Prediction of Electronic Density of States

    Victor Fung, Panchapakesan Ganesh, Bobby G. Sumpter

    Maqola20222 iqtibos
    ABI

  25. Periodic Graph Transformers for Crystal Material Property Prediction

    Keqiang Yan, Yi Liu, Yuchao Lin +1

    Preprint20222 iqtibos
    ABI