bookmarks (hide)7
- Deep learning for climate modeling. Contribute to monocongo/climate_learn development by creating an account on GitHub.
publications (hide)494
- Milets@KDD, (2022)
- (2015)
- CreateSpace, Scotts Valley, CA, (2009)
- R Foundation for Statistical Computing, Vienna, Austria, (2022)
- https://opendata.dwd.de/climate_environment/CDC/grids_germany/multi_annual/, (2020)
- https://geodatenonline.bayern.de/geodatenonline/seiten/dgm_info, (1996)
- https://www.lfu.bayern.de/umweltdaten/index.htm, (2017)Unpublished.
- science, 289 (5487): 2068--2074 (2000)
- Current Climate Change Reports, 2 (4): 211--220 (2016)
- First International Workshop on Learning with Imbalanced Domains: Theory and Applications, LIDTA@PKDD/ECML 2017, 22 September 2017, Skopje, Macedonia, volume 74 of Proceedings of Machine Learning Research, page 36--50. PMLR, (2017)
- Journal of Geophysical Research: Atmospheres, 123 (22): 12--543 (2018)
- Proceedings of the 29th ACM International Conference on Multimedia, page 2167--2175. (2021)
- International conference on medical image computing and computer-assisted intervention, page 263--273. Springer, (2020)
- arXiv preprint arXiv:1909.08053, (2019)
- arXiv preprint arXiv:1810.04805, (2018)
- Communications of the ACM, 60 (6): 84--90 (2017)
- Proceedings of the IEEE conference on computer vision and pattern recognition, page 2818--2826. (2016)
- (2015)Software available from tensorflow.org.
- Proceedings of the 23rd international conference on Machine learning, page 185--192. (2006)
- Journal of complexity, 6 (2): 192--198 (1990)
