Ding Ning

Publications

Vetrova, V., Ning, D., Bryan, K. R., & Koh, Y. S. (2025, March 15). Forecasting monthly-to-seasonal sea surface temperatures and marine heatwaves with graph neural networks and diffusion methods [Paper presentation]. EGU General Assembly 2025. Vienna, Austria.

Ning, D. (2024). Moananet: A deep learning framework for global short-to-long-term sea surface temperature anomaly and marine heatwave forecasts [Doctoral thesis,University of Canterbury]

Ning, D., Vetrova, V., Bryan, K. R., Koh, Y. S., Voskou, A., Kouagou, N. J., & Sharma, A. (2024, 09). Diving deep: Forecasting sea surface temperatures and anomalies [Paper presentation]. ECML PKDD 2024 Discovery Track, Vilnius, Lithuania.

Koh, Y. S., Bifet, A., Bryan, K. R., Cassales, G., Graffeuille, O., Lim, N., Mourot, P., Ning, D., Pfahringer, B., Vetrova, V., & Gomes, H. M. (2024). Time-evolving data science and artificial intelligence for advanced open environmental science (TAIAO) programme. In Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI-24) Special Track on AI for Good (Ed.), IJCAI 2024 AI for Good Track (pp. 7314-7322).

Ning, D., Vetrova, V., Bryan, K. R., & Koh, Y. S. (2024). Harnessing the power of graph representation in climate forecasting: Predicting global monthly mean sea surface temperatures and anomalies. Earth and Space Science, 11(3), 1-44.

Ning, D., Vetrova, V., & Bryan, K. R. (2023, 05). Graph-based deep learning for sea surface temperature forecasts [Poster presentation]. ICLR 2023 Workshop on Tackling Climate Change with Machine Learning, Kigali, Rwanda.

Ning, D., Vetrova, V., Bryan, K. B., & Delaux, S. (2021, 07). Deep learning for spatiotemporal anomaly forecasting: a case study of marine heatwaves [Poster presentation]. ICML 2021 Workshop on Tackling Climate Change with Machine Learning, Vienna, Austria.