Extreme Event Likelihoods with Guided Generative Models

Guided diffusion models can be used to efficiently sample rare, high-impact climate events like tropical cyclones without requiring brute-force Monte Carlo runs. The key challenge is correcting for the oversampling bias introduced by guidance — solved here via an odds ratio between guided and unguided distributions, enabling importance sampling. Using NVIDIA's cBottle climate emulator and Earth2Studio, the workflow generates tropical cyclone atmospheric states near a specified location and computes log-odds ratios to estimate true event likelihoods. This approach reduced standard error by 25% compared to naive Monte Carlo sampling. The technique generalizes beyond climate to any domain where rare events dominate risk, including finance, aerospace, and materials science.

Source: https://developer.nvidia.com/blog/extreme-event-likelihoods-with-guided-generative-models. 8 Sync News only summarizes and links out; content copyright belongs to the authors and original sources.