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TailBooster not only generates synthetic data for rare extreme events but also ensures that the data adheres to operational constraints, leading to substantial improvements in predictive accuracy.
Overcome the scarcity of rare flight diversion events by using optimized generative models to create synthetic data that substantially improves prediction accuracy.
Synthetic flight data generated by generative models can train flight delay prediction models with accuracy comparable to those trained on real data, unlocking new possibilities for predictive modeling in air transportation.
