Core Concepts
Zebra, a novel generative autoregressive transformer, effectively solves parametric PDEs by leveraging in-context information during both pretraining and inference, eliminating the need for gradient adaptation and enabling uncertainty quantification.
Stats
Zebra achieves a confidence level exceeding 95% for temperature values greater than 0.5 in uncertainty quantification.