ConclusionsðŠķ
ðŪ Future Implementations
- Explore ways to implement adaptive sampling.
- Train models with learnable frequency \(\omega\).
- Explicitly condition the network on \(\omega\).
- Explore richer low-fidelity physics contraints and Hamiltonian structure preservation (e.g., an energy conservation loss term).
- Explore ways to introduce inductive biases (limitations).