Congbo Song - Research output - Research Explorer The University of Manchester

Phone+44(0)7388617748
Emailcongbo.songmanchester.acuk
Websitehttps://congbo.site, https://m-edal.github.io

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32 Article
1 Conference contribution
1 Poster
1 Letter
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- 1 Review article
- 1 Other contribution

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2024
Using explainable machine learning to better understand source and process contributions to atmospheric bio-aerosol
Zhang, H., Song, C., Topping, D., Crawford, I., Gallagher, M., Chan, M. N., Lee, H. B. M., Xing, S., Ng, T. H. & Tai, A., 14 Apr 2024, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16338, . EGU24-16338
Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

Open Access