Applied Stochastic Differential Equations

@inproceedings{Srkk2019AppliedSD,
  title={Applied Stochastic Differential Equations},
  author={S. S{\"a}rkk{\"a} and A. Solin},
  year={2019}
}
The topic of this book is stochastic differential equations (SDEs). As their name suggests, they really are differential equations that produce a different “answer” or solution trajectory each time they are solved. This peculiar behaviour gives them properties that are useful in modeling of uncertainties in a wide range of applications, but at the same time it complicates the rigorous mathematical treatment of SDEs. The emphasis of the book is on applied rather than theoretical aspects of SDEs… Expand
Variational Bridge Constructs for Grey Box Modelling with Gaussian Processes
Black-Box Inference for Non-Linear Latent Force Models
Deterministic Inference of Neural Stochastic Differential Equations
Linear-Time Probabilistic Solutions of Boundary Value Problems
Sampling of Stochastic Differential Equations using the Karhunen-Loève Expansion and Matrix Functions
Stable Implementation of Probabilistic ODE Solvers
Safety Verification for Random Ordinary Differential Equations
Neural ODEs with stochastic vector field mixtures
State-Space Gaussian Process for Drift Estimation in Stochastic Differential Equations
  • Zheng Zhao, Filip Tronarp, R. Hostettler, S. Särkkä
  • Computer Science, Mathematics
  • ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • 2020
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References

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