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Sometimes one needs stochastic input in only some of your differential equations.
If the noise is, e.g., also correlated, that means constructing a CorrelatedWienerProcess
with a very large correlat…
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There are several extensions of "B-series for Runge-Kutta methods" that could also be implemented in this package:
- [ ] P-series for partitioned methods (see HNW II.15) and NB-series for additive …
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Drift:
- [ ] Explicit Runge-Kutta methods for the drift computation
- [x] Butcher-Tableau
- [x] RK4
- [ ] ~~Specialized for RK2 (Heun and Ralston)~~
- [ ] ~~Runge—Kutta—Nyström me…
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The Navier-Stokes equations, which describe the motion of fluid substances such as liquids and gases, are fundamental to the field of fluid dynamics. However, several challenging problems related to t…
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I'd like to brighten the possibility of integrating stochastic delay ODEs, if possible.
Can the approach used in, https://github.com/Zulko/ddeint/blob/master/ddeint/ddeint.py, be adapted for sdeint? …
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sdeint is a pure Python package to integrate stochastic differential equations. When I try to install it I get a message like it is installed, but it is not.
I know it works on iPad, because (with di…
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Thank you for your excellent work on deformable image registration! When I read your paper, it confuses me that the meanings of Ldiffuse. In your paper, Ldiffuse is seemed to predict the noise (e) add…
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# Analytic Gaussian Process Analysis Framework
1. Kernel Representation Module
- Implement your exact form of the kernel for the Hardy Z-function
- Generalize to handle other analytic kerne…
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### **Glycolysis**
- **Accuracy**: The model correctly represents glycolysis occurring in the cytoplasm, where each glucose molecule is converted into two pyruvate molecules, yielding a net gain of…
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Read this paper: https://arxiv.org/abs/2402.06079