** The dataset for this project is publicly available and can be accessed at (https://zenodo.org/records/14752305)**
** The reference for the sea ice model data can be found at https://gmd.copernicus.org/articles/12/3745/2019/ **
[1] A. Sampath, O. Faruque, A. Khan, V. Janeja and J. Wang, "Physics-Informed Machine Learning for Sea Ice Thickness Prediction," 2024 IEEE International Conference on Knowledge Graph (ICKG), Abu Dhabi, United Arab Emirates, 2024, pp. 325-333. doi: 10.1109/ICKG63256.2024.00048.
Keywords:
- Predictive models
- Transformers
- Arctic sea ice
- Long short term memory
- Physics-informed Machine Learning
- Sea Ice Thickness Prediction
- Long Short Term Memory (LSTM)
- Gated Recurrent Units (GRU)
- Layer-wise Relevance Propagation (LRP)