1 Introduction  
2 Imbalanced Classification  
2.1 Training Distribution  
2.2 Model Logits and Weights  
2.3 Representation Space  
2.4 Non-uniform Test Distribution  
3 Imbalanced Regression  
3.1 Synthetic Rare Samples  
3.2 Label Space Smoothing  
3.3 Representation Space Calibration  
3.4 Loss Re-Weighting  
4 Representation Learning  
4.1 Positive and Negative Pairs  
4.2 Positive Pairs Only  
4.3 Generative Features  
4.4 Representation Learning on Tabular Data  
5 SEP Forecasting  
5.1 Primarily CME Features  
5.2 Primarily X-Ray Features  
5.3 Primarily Active Region Features  
5.4 Primarily Solar Radio Flux Features  
6 Conclusion