-
Data-Driven Koopman Framework for Modeling Complex Dynamical Systems
A Seminar by Yuanchao Xu (Kyoto University, Japan)
-
Harnessing the Power of Neural Operators with Automatically Encoded Conservation Laws
Using the theory of differential forms to hard-code divergence-free constraints in neural operators
-
Clawno copie.mdzone
-
Efficient Dynamics Modeling in Interactive Environments with Koopman Theory
Using Koopman theory to learn a linear dynamics in a latent space
-
Neural operators and chaotic attractors
Training neural operators to preserve invariant measures of chaotic attractors