4 papers - avg viability 4.0
A novel data sampling method for neural simulators that improves rollout accuracy by intelligently selecting training data based on model gradients and temporal coverage.
A new class of operator networks that leverage in-context learning to solve complex higher-order partial differential equations with qualitative accuracy.
This paper provides theoretical guarantees for the accuracy of neural network solutions to partial differential equations by connecting residual errors to solution-space errors.