#dynamical systems

Researchers reveal a new method using latent vector fields to understand how neural autoencoders balance memorization and generalization, enhancing interpretability without modifying models.

UT Austin researchers introduce Panda, a novel pretrained model trained on 20,000 chaotic systems that excels at zero-shot forecasting for complex nonlinear dynamics, including real-world and PDE scenarios.