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Found 3 papers, 2 papers with code
Ensemble and Mixture-of-Experts DeepONets For Operator Learning
We also present a spatial mixture-of-experts (MoE) DeepONet trunk network architecture that utilizes a partition-of-unity (PoU) approximation to promote spatial locality and model sparsity in the operator learning problem.
Accelerated Training of Physics-Informed Neural Networks (PINNs) using Meshless Discretizations
Finally, we also demonstrate that similar results can be obtained for the PINN solution to the heat equation (a space-time problem) by discretizing the spatial derivatives using RBF-FD and using automatic differentiation for the temporal derivative.
Beyond modeling: NLP Pipeline for efficient environmental policy analysis
As we enter the UN Decade on Ecosystem Restoration, creating effective incentive structures for forest and landscape restoration has never been more critical.
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