Track new results across pure and applied mathematics.
Search papers, labs, and topics across Lattice.
Affiliation:
2
0
3
Neural operators can now learn directly from noisy, low-cost Monte Carlo estimates, achieving $10^4$-$10^5\times$ speedups for particle transport problems without sacrificing accuracy.
Physics-informed neural operators can now generalize to unseen physical regimes and extrapolate in time by explicitly encoding the underlying operator structure and decomposing PDEs into interpretable components.