Stochastic Partial Differential Equations
PulseAugur coverage of Stochastic Partial Differential Equations — every cluster mentioning Stochastic Partial Differential Equations across labs, papers, and developer communities, ranked by signal.
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Deep learning algorithm offers accurate SPDE solutions in high dimensions
A new research paper introduces a deep learning-based algorithm for approximating solutions to stochastic partial differential equations (SPDEs). This method utilizes neural networks to estimate SPDE solutions based on …
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New SON framework quantifies uncertainty in SPDEs
Researchers have developed a new framework called the Stochastic Operator Network (SON) for quantifying uncertainty in stochastic partial differential equations (SPDEs). This method combines Deep Operator Networks with …
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New Kalman Filter framework models complex time-series data on cell complexes
Researchers have developed a new topology-aware state space framework for inferring latent dynamics from complex time-series data. This approach utilizes stochastic partial differential equations on cell complexes to mo…
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Martingale Neural Operators learn stochastic marginals via Doob-Meyer factorization
Researchers have developed a new neural operator architecture called Martingale Neural Operator (MNO) designed to handle stochastic partial differential equations (SPDEs). Unlike existing deterministic operators that co…