Missing data of intelligent scientific instruments

Machine Learning


  • Vaswani, A. et al. All you need is attention. in Advances in neural information processing systems Vol. 30 (edited by Guyon, I. et al.) https://proceedings.neurips.cc/paper_files/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf (Curran, 2017).

  • Preprint in Henighan, T. et al. arXiv https://doi.org/10.48550/arXiv.2010.14701 (2020).

  • Jumper, J. et al. nature 596583–589 (2021).

    Article PubMed PubMed Central Google Scholar

  • Preprint in Kim, MJ et al. arXiv https://doi.org/10.48550/arXiv.2406.09246 (2024).

  • OECD. Artificial intelligence in science: research challenges, opportunities, and the future https://www.oecd.org/en/publications/artificial-intelligence-in-science_a8d820bd-en.html (OECD, 2023).

  • Boyko, D.A., McKnight, R., Klein, B., Gomez, G. nature 624570–578 (2023).

    Article PubMed PubMed Central Google Scholar

  • New Jersey Szymanski et al. nature 62486–91 (2023).

    Article PubMed PubMed Central Google Scholar

  • Eisenstein, M. nut. method 171075–1079 (2020).

    Article PubMed Google Scholar

  • AE Carpenter, BA Cimini, KW Eliceiri. nut. method 20962–964 (2023).

    Article PubMed PubMed Central Google Scholar

  • Griffin, C., Wallace, D., Mateos-Garcia, J., Schieve, H. & Kohli, P. A new golden age of discovery: Seizing the opportunity of AI for Science. AI policy outlook https://www.aipolicyperspectives.com/p/a-new-golden-age-of-discovery (2024).

  • Preprint in Villalobos, P. et al. arXiv https://doi.org/10.48550/arXiv.2211.04325 (2024).

  • Manning, C., Raghavan, P., Schutze, H. Information search overview (Cambridge University Press, 2009).

  • Zulueta-Coarasa, T. et al. nut. method twenty two2245–2252 (2025).

    Article PubMed Google Scholar

  • Skowronek, P., Nawalgaria, A. & Mann, M. Preprint of bioRxiv https://doi.org/10.1101/2025.10.05.680425 (2025).

  • Preprint in Douillard, A. et al. arXiv https://doi.org/10.48550/arXiv.2311.08105 (2023).



  • Source link