Асосий контентга ўтиш
AkademIndex

Маҳсулотлар

Ишлаб чиқувчилар учун

AkademBaseЭкотизим учун очиқ API
← Ишга қайтиш

Ушбу иш иқтибос қилган ишлар

37 та иш

Иш: Structure to Property: Chemical Element Embeddings 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

    Мақола201312 иқтибос
    ABI

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

    Muhammad Naveed Akhter, Saad Mekhilef, Hazlie Mokhlis +1

    Мақола20194 иқтибос
    ABI

  3. Applications of machine learning in drug discovery and development

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

    Шарҳ мақола20194 иқтибос
    ABI

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

    Takashi Toyao, Zen Maeno, Satoru Takakusagi +3

    Мақола20194 иқтибос
    ABI

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

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

    Мақола20204 иқтибос
    ABI

  6. Machine learning for alloys

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

    Шарҳ мақола20214 иқтибос
    ABI

  7. On representing chemical environments

    Albert P. Bartók, Risi Kondor, Gábor Cśanyi

    Мақола20133 иқтибос
    ABI

  8. The atomic simulation environment—a Python library for working with atoms

    Ask Hjorth Larsen, Jens Jørgen Mortensen, Jakob Blomqvist +31

    Мақола20173 иқтибос
    ABI

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

    Tian Xie, Jeffrey C. Grossman

    Мақола20183 иқтибос
    ABI

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

    Yuma Iwasaki, Ichiro Takeuchi, Valentin Stanev +10

    Мақола20193 иқтибос
    ABI

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

    Simon J. L. Billinge

    Мақола20193 иқтибос
    ABI

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

    Chi Chen, Weike Ye, Yunxing Zuo +2

    Мақола20193 иқтибос
    ABI

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

    Yue Liu, Biru Guo, Xinxin Zou +2

    Мақола20203 иқтибос
    ABI

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

    Shuo Zhang, Yang Liu, Lei Xie

    Препринт20203 иқтибос
    ABI

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

    Shufeng Kong, Francesco Ricci, Dan Guevarra +3

    Мақола20223 иқтибос
    ABI

  16. Unified representation of molecules and crystals for machine learning

    Haoyan Huo, Matthias Rupp

    Мақола20223 иқтибос
    ABI

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

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

    Шарҳ мақола20223 иқтибос
    ABI

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

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

    Мақола20142 иқтибос
    ABI

  19. Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces

    Jörg Behler, Michele Parrinello

    Мақола20072 иқтибос
    ABI

  20. PhysNet: A Neural Network for Predicting Energies, Forces, Dipole Moments, and Partial Charges

    Oliver T. Unke, Markus Meuwly

    Мақола20192 иқтибос
    ABI

  21. Learning the electronic density of states in condensed matter

    Chiheb Ben Mahmoud, Andrea Anelli, Gábor Cśanyi +1

    Мақола20202 иқтибос
    ABI

  22. Benchmarking graph neural networks for materials chemistry

    Victor Fung, Jiaxin Zhang, Eric Juarez +1

    Мақола20212 иқтибос
    ABI

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

    Zhantao Chen, Nina Andrejevic, Tess Smidt +7

    Мақола20212 иқтибос
    ABI

  24. Machine learning potentials for extended systems: a perspective

    Jörg Behler, Gábor Cśanyi

    Мақола20212 иқтибос
    ABI

  25. Сарлавҳасиз

    Бошқа2 иқтибос
    ABI