Special Session on Rare Events Detection at IAMG2023 is calling for abstract submission.
The session will discuss recent advances in data-driven modeling approaches for detecting rare events, i.e., events with a significant impact and long-lasting consequences that are uncommon in frequency.
We will discuss current best practices for rare event detection in geosciences and, more specifically, in geoengineering. The session aims to present new proposals and findings in data preprocessing, feature engineering, rebalancing, application of statistical or machine learning methods, and demonstrations of progress in rare event detection that can promote a proactive approach to risk management.
The topics of interest:
1. overviews of methods and recommended workflows for handling data sparsity and uncertainty;
2. reviews of new findings and techniques for rare events' detection and recommendations on data preprocessing methods that help to ensure both data quality and novelty in patterns;
3. reports on how various methods for handling data imbalance affect the accuracy of forecasting data-driven models;
4. approaches used for detecting perceptions and biases in data labeling and interpretations;
5. demonstrations of methods and tools successfully employed for risk modeling and rare event detection.
The follow-up papers will be recommended for publishing in "Computers & Geosciences"