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Stochastic ordinary and partial differential equations generalize the concepts of ordinary and partial differential equations to the setting where the unknown is a stochastic process.

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Uniqueness of the solution to stochastic differential equation

First for the case of time-independent coefficients (autonomous). A good setting for this question is the Feller-explosion test (see here Is this process strictly positive? for related question). The …
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When and why do we require the condition that :"a subset bounded from below and has no accum...

From the references mentioned in the comments , (section 4.4,"Renormalisation of parabolic stochastic PDEs") (RP) and (section 6.1,"Introduction to regularity structures") (IRS), we first start from t …
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1 vote

Why does the correct scaled dimension for SPDEs count time as two dimensions?

the links on the video and notes are not there. But indeed as they explain in "Stochastic PDEs, Regularity Structures, and Interacting Particle Systems" at page 13, the main reason is that the Schaude …
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1 vote

Stochastic differential equations with correlated Brownian Motions

As mentioned in the comments you simply need to do a transformation. Here in "Modelling the Stochastic Correlation" pg.23 they give the concrete transformation You replace your SDE by the above. Then …
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0 votes

Solving SDE with sign function in drift term?

Indeed, as mentioned in the comments one can return to a geometric BM. We start with the Lamperti transformation 2.1.5/2.1.6 from "The Lamperti Transform" by de Boer. First using Ito to compute for ge …
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1 vote

Explicit solution for a simple SDE?

Here we can do a time-change to get a time-changed Brownian motion solution. see here Characterization of martingale diffusions ending in $\{-1,1\}$ This is also done carefully in Shreves-Karatzas sec …
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Martingale representation of time-changed Brownian motion

Indeed as mentioned in the comments and in the blog here https://almostsuremath.com/2010/04/20/time-changed-brownian-motion/ for $\theta(t)=\frac{t}{1-t}$, we get that $B_{\theta(t)}\stackrel{d}{=}\i …
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1 vote

Invariant measure theory for SPDEs with distributional solutions (Hilbert versus Polish)

The situation can be a bit trickier because we are dealing with distribution valued objects and thus the need to first smoothen the equations. For example, as explained in "Fluctuation and Rate of Con …
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1 vote

Well-posedness of a stochastic differential equation in the Stratonovich sense

As mentioned in this answer, the conversion to Stratonovich SDE is the following: You are considering the Stratonovich SDE $$ dX = h(X) \, dt + \gamma (X) \circ dW, $$ where I suppose the following h …
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2 votes

Giving meaning to and solving a second-order stochastic differential equation with white noise

Here we are assuming that by white noise $W(r)$ the OP meant $$W(r)=\frac{dB_{r}}{dr}.$$ If meant something different, please comment below. Then one interpretation can be done by letting $X=\frac{dT} …
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Do regularity structures involve infinite "Taylor" series?

So one good start is "Rough Stochastic PDEs". Here Hairer builds a notion of an SPDE solution using rough paths first building the invariant solution $\psi_{t}(x)$ and lifting to a rough path $\psi_{ …
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Convergence of a continuous time stochastic gradient descent algorithm

here "An SDE perspective on stochastic convex optimization" they study these type of SDEs (Stochastic gradient descent) and basically ask bounded and an L2 condition for gamma_t in theorem 3.1. Here …
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Expected value of a stochastic integral expression

Based on the comment of being interested in the hitting time for OU, it turns out that finding its density is still open as mentioned here: On the First Hitting Time Density of an Ornstein-Uhlenbeck P …
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Weak solutions of linear parabolic PDEs and corresponding SDEs

One of the latest conditions on $\mu,\sigma$ are from "A Numerical Method for SDEs with Discontinuous Drift": This result states that the SDE (1) ($dX_t = \mu(X_t)dt + \sigma(X_t)dW$) admits a unique …
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How to rigorously prove that this sequence of stochastic processes converges to a determinis...

I am guessing in "The particular thing I'm trying to prove is that,..." you are talking about the convergence of discrete generator to continuous one. The natural topology for these questions is Skoro …
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