The Stochastic Operator Network learns mean solutions and uncertainty for SPDEs from noisy data by merging DeepONet structure with stochastic neural networks, trained via Hamiltonian loss and the Stochastic Maximum Principle.
L´ evy backward sde filter for jump diffusion processes and its applications in material sciences
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ML 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Diffusion-Based Stochastic Operator Networks for Uncertainty Quantification in Stochastic Partial Differential Equations
The Stochastic Operator Network learns mean solutions and uncertainty for SPDEs from noisy data by merging DeepONet structure with stochastic neural networks, trained via Hamiltonian loss and the Stochastic Maximum Principle.