Balance Point-wise Accuracy and Structure

Background: The current framework optimizes a single combined loss function, potentially leading to a trade-off where optimizing point-wise accuracy might compromise the preservation of large-scale spatial structures.

Question / Future Work: Develop and investigate multi-objective optimization strategies that explicitly balance the minimization of point-wise prediction errors (like MSE) with the preservation of global structural fidelity (like SSIM or physical invariants) in the forecasts.

Why It Matters: Addressing this trade-off is crucial for scientific applications where both local numerical correctness and global structure/conservation properties are important.

Evidence: Furthermore, the observed trade-off between minimizing point-wise prediction errors and preserving structural fidelity in spatiotemporal data remains an open challenge. Future research could focus on multi-objective optimisation strategies that balance numerical accuracy with the preservation of global structures.