1. Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G., Davis, A., Dean, J., Devin, M., Ghemawat, S., Goodfellow, I., Harp, A., Irving, G., Isard, M., Jia, Y., Jozefowicz, R., Kaiser, L., Kudlur, M., Levenberg, J., Mańe, D., Monga, R., Moore, S., Murray, D., Olah, C., Schuster, M., Shlens, J., Steiner, B., Sutskever, I., Talwar, K., Tucker, P., Vanhoucke, V., Vasudevan, V., Víegas, F., Vinyals, O., Warden, P., Wattenberg, M., Wicke, M., Yu, Y., Zheng, X., 2015. TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. http://tensorflow.org/.software available from tensorflow.org.
2. Changes in plant community composition lag behind climate warming in lowland forests;Bertrand;Nature,2011
3. Energy Efficiency Vision 2050: how will new societal trends influence future energy demand in the European countries?;Brugger;Energy Pol.,2021
4. Accelerated increase in vegetation carbon sequestration in China after 2010: A turning point resulting from climate and human interaction;Chen;Glob. Change Biol.,2021
5. Health risk assessment of potentially harmful elements in subsidence water bodies using a Monte Carlo approach: an example from the Huainan coal mining area;Chen;China. Ecotox. Environ. Safe.,2019