“To explore, to criticize, to learn…”
The papers we are reading and discussing.
2023
[8] Song, K., Fang, C., Jacinthe, P. A., Wen, Z., Liu, G., Xu, X., … & Lyu, L. (2021). Climatic versus anthropogenic controls of decadal trends (1983–2017) in algal blooms in lakes and reservoirs across China. Environmental science & technology, 55(5), 2929-2938. (Led by Xidong Chen)
[7] Rentschler, J., & Leonova, N. (2023). Global air pollution exposure and poverty. Nature Communications, 14(1), 4432. (Led by Wenbo Yu)
[6] Donovan, G. H., Gatziolis, D., Derrien, M., Michael, Y. L., Prestemon, J. P., & Douwes, J. (2022). Shortcomings of the normalized difference vegetation index as an exposure metric. Nature Plants, 8(6), 617-622. (Led by Binley)
[5] Tucker, C., Brandt, M., Hiernaux, P., Kariryaa, A., Rasmussen, K., Small, J., … & Fensholt, R. (2023). Sub-continental-scale carbon stocks of individual trees in African drylands. Nature, 615(7950), 80-86. (Led by Ziming Li)
[4] Lee, J., Brooks, N. R., Tajwar, F., Burke, M., Ermon, S., Lobell, D. B., … & Luby, S. P. (2021). Scalable deep learning to identify brick kilns and aid regulatory capacity. Proceedings of the National Academy of Sciences, 118(17), e2018863118. (Led by Wenbo Yu)
[3] Yeh, C., Meng, C., Wang, S., Driscoll, A., Rozi, E., Liu, P., … & Ermon, S. (2021). Sustainbench: Benchmarks for monitoring the sustainable development goals with machine learning. arXiv preprint arXiv:2111.04724. (Led by Wenbo Yu)
[2] Rumpf, S. B., Gravey, M., Brönnimann, O., Luoto, M., Cianfrani, C., Mariethoz, G., & Guisan, A. (2022). From white to green: Snow cover loss and increased vegetation productivity in the European Alps. Science, 376(6597), 1119-1122. (Led by Ying Tu)
[1] Ratledge, N., Cadamuro, G., de la Cuesta, B., Stigler, M., & Burke, M. (2022). Using machine learning to assess the livelihood impact of electricity access. Nature, 611(7936), 491-495. (Led by Shengbiao Wu)