Distribution Prediction

Distribution prediction focuses on modeling the probability distribution of an outcome variable, rather than just predicting a single point estimate, thereby providing a more comprehensive understanding of uncertainty. Current research emphasizes improving the accuracy and efficiency of these predictions, particularly using large language models and ensemble methods, and exploring how to best leverage information from both prediction confidence and the overall distribution of predictions. This enhanced understanding of uncertainty has significant implications for various fields, improving the reliability of predictions in applications ranging from image compression and natural language processing to medical diagnosis and survival analysis.