Let $X\colon \Omega \to \mathbb R$ a real valued random variable with continuous p.d.f. Then if $F_X$ is its c.d.f., the random variable $F_X(X)$ is uniformly distributed on $(0,1)$.
Now suppose $X\colon \Omega \to \mathbb R^d$ is multivariate, still with continuous p.d.f. My question is can we construct a continuous bijection $F\colon \mathbb R^d\to (0,1)^d$ such that $F(X)$ is uniformly distributed on $(0,1)^d$?
We could try $F= (F_{X_1},\dots,F_{X_d})$, where $F_{X_i}$ are the marginal c.d.fs. But this will only be uniformly distributed on $(0,1)^d$ if $X_1,\dots,X_d$ are independent. Otherwise there is additional information in the interdependence between components, captured by the copula $C\colon (0,1)^d\to (0,1)$.
Note the difference with these StackExchange questions: When is a measure the pushforward of another measure? When does a measurable function exist with a given distribution? which work under more general settings and do not require a (continuous) bijection.
Any help or references are appreciated. It feels like this problem must have been studied, but I haven't been able to find much online so far.