2018 CSDMS Annual Meeting:
With Artificial Intelligence & Machine Learning - What Lies Ahead for Earth Surface Modeling ?
A Forum, 1030-1230pm, 24th May 2018, SEEC Room ### Convened by Chris JENKINS (INSTAAR, Boulder CO) and Jeff OBELCZ (NRL, Stennis, MS)
Questions for the Forum
- What can AI and ML currently do that might benefit Earth Surface Dynamics Modeling ?
- What is the relationship between Process Modelling and AI/ML ?
- How should CSDMS Community Respond to the Appearance of AI/ML
- What Earth Surface Dynamics Modeling-related tasks are not suited for AI/ML? Why?
- Participants can share URL's here to papers that discuss the workings of AI/ML and applications in fields such as ours. Some papers are also relevant to questions for the forum (above).
Jones, N. 2018. How machine learning could help to improve climate forecasts. Nature 548, 379–380 (24 August 2017) doi:10.1038/548379a .
Abbot, J. & Marohasy,J. 2013. The Application Of Artificial Intelligence For Monthly Rainfall Forecasting In The Brisbane Catchment, Queensland, Australia. WIT Transactions on Ecology and the Environment, 172, 125 - 135. DOI:10.2495/RBM130111
Karpatne, A., et al., 2017. Machine Learning for the Geosciences: Challenges and Opportunities. Workshop on Mining Big Data in Climate and Environment (MBDCE 2017), 17th SIAM International Conference on Data Mining (SDM 2017).
Displays during the Forum
- Posters, and printed materials for distribution will be available at the event
Online Resources for the Forum
- This Wiki will serve Abstracts, URL's, Posters, Images supplied by participants before and during the meeting
Dateline: CJ 12Feb2018Small text