Parsa Esmati

SEA: State-Exchange Attention for High-Fidelity Physics Based Transformers

Current approaches using sequential networks have shown promise in estimating field variables for dynamical systems, but they are often limited by high rollout errors. The unresolved issue of rollout error accumulation results in unreliable estimations as the network predicts further into the future…