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48 ta ish

Ish: Accurate classification of materials with elEmBERT: Element embeddings for chemical benchmarks

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

    Anubhav Jain, Shyue Ping Ong, Geoffroy Hautier +8

    Maqola201312 iqtibos
    ABI

  2. AI-Assisted Pipeline for Dynamic Generation of Trustworthy Health Supplement Content at Scale

    Kefallinos, Dionysios, Alexandris, Georgios, Maras, Alexis +5

    Preprint201811 iqtibos
    ABI

  3. Scikit-learn: Machine Learning in Python

    PedregosaFabian, VaroquauxGaël, GramfortAlexandre +13

    Maqola20116 iqtibos
    ABI

  4. MoleculeNet: a benchmark for molecular machine learning

    Zhenqin Wu, Bharath Ramsundar, Evan N. Feinberg +5

    Maqola20176 iqtibos
    ABI

  5. Crystallography Open Database – an open-access collection of crystal structures

    S. Gražulis, Daniel Chateigner, Robert T. Downs +7

    Maqola20094 iqtibos
    ABI

  6. 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

  7. Applications of machine learning in drug discovery and development

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

    Sharh maqola20194 iqtibos
    ABI

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

    Takashi Toyao, Zen Maeno, Satoru Takakusagi +3

    Maqola20194 iqtibos
    ABI

  9. 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

  10. Efficient Estimation of Word Representations in Vector Space

    Tomáš Mikolov, Kai Chen, Greg S. Corrado +1

    Preprint20133 iqtibos
    ABI

  11. On representing chemical environments

    Albert P. Bartók, Risi Kondor, Gábor Cśanyi

    Maqola20133 iqtibos
    ABI

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

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

    Maqola20173 iqtibos
    ABI

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

    Tian Xie, Jeffrey C. Grossman

    Maqola20183 iqtibos
    ABI

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

    Yuma Iwasaki, Ichiro Takeuchi, Valentin Stanev +10

    Maqola20193 iqtibos
    ABI

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

    Simon J. L. Billinge

    Maqola20193 iqtibos
    ABI

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

    Chi Chen, Weike Ye, Yunxing Zuo +2

    Maqola20193 iqtibos
    ABI

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

    Yue Liu, Biru Guo, Xinxin Zou +2

    Maqola20203 iqtibos
    ABI

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

    Shuo Zhang, Yang Liu, Lei Xie

    Preprint20203 iqtibos
    ABI

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

    Shufeng Kong, Francesco Ricci, Dan Guevarra +3

    Maqola20223 iqtibos
    ABI

  20. Unified representation of molecules and crystals for machine learning

    Haoyan Huo, Matthias Rupp

    Maqola20223 iqtibos
    ABI

  21. 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

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

    Oliver T. Unke, Markus Meuwly

    Maqola20192 iqtibos
    ABI

  23. Benchmarking graph neural networks for materials chemistry

    Victor Fung, Jiaxin Zhang, Eric Juarez +1

    Maqola20212 iqtibos
    ABI

  24. Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space

    Katja Hansen, Franziska Biegler, Raghunathan Ramakrishnan +4

    Maqola20152 iqtibos
    ABI

  25. Structure to Property: Chemical Element Embeddings for Predicting Electronic Properties of Crystals

    Shokirbek Shermukhamedov, Dilorom Mamurjonova, Thana Maihom +1

    MaqolaMachine Learning in Materials ScienceJournal of Chemical Information and Modeling20241 iqtibos
    ABI