4 papers · 1 filter
Comparing and Contrasting DLWP Backbones on Navier-Stokes and Atmospheric Dynamics
Matthias Karlbauer, Danielle C. Maddix, Abdul Fatir Ansari +5
A large number of Deep Learning Weather Prediction (DLWP) architectures -- based on various backbones, including U-Net, Transformer, Graph Neural Network, and Fourier Neural Operat…
DICE: Discrete inverse continuity equation for learning population dynamics
Tobias Blickhan, Jules Berman, Andrew Stuart +1
We introduce the Discrete Inverse Continuity Equation (DICE) method, a generative modeling approach that learns the evolution of a stochastic process from given sample populations…
Gradient-Free Generation for Hard-Constrained Systems
Chaoran Cheng, Boran Han, Danielle C. Maddix +4
Generative models that satisfy hard constraints are critical in many scientific and engineering applications, where physical laws or system requirements must be strictly respected.…
Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs
S. Chandra Mouli, Danielle C. Maddix, Shima Alizadeh +4
Existing work in scientific machine learning (SciML) has shown that data-driven learning of solution operators can provide a fast approximate alternative to classical numerical par…