Questions tagged [optimal-transportation]

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Lipschitz approximation of a probability measure with finite $1$-st moment by the ones with finite $p$-th moment

For $p \in [1, \infty)$, let $\mathcal P_p (\mathbb{R^d})$ be the space of Borel probability measures on $\mathbb R^d$ with finite $p$-th moment. We endow $\mathcal P_p (\mathbb{R^d})$ with the ...
Akira's user avatar
  • 851
7 votes
1 answer
339 views

Proving the inequality involving Hausdorff distance and Wasserstein infinity distance

Prove the inequality $$d_{H}(\mathrm{spt}(\mu),\mathrm{spt}(\nu))\leq W_{\infty}(\mu,\nu)$$ where $d_H$ denotes the Hausdorff distance between the supports of the measures $\mu$ and $\nu$, and $W_\...
Luna Belle's user avatar
3 votes
0 answers
105 views

Are 1-Wasserstein and 2-Wasserstein distances between multivariate normal distributions equivalent?

The $p$-Wasserstein between two measures $\nu_1$ and $\nu_2$ on $X$ is given by $$W^p_p(\nu_{1},\nu_{2})=\underset{\pi\in\Gamma(\nu_{1},\nu_{2})}{\inf}\int_{\mathbf{\mathcal{X}}^{2}}d(x,y)^p\pi(dx,dy)$...
Vladimir Zolotov's user avatar
0 votes
0 answers
93 views

Some stability and estimate of the optimal transport map (Brenier map)

Let $\mu$ and $\nu$ be two probability measures with finite moments (in $\mathcal{P}_2(\mathbb{R})$) equipped with 2-Wasserstein distance. Let $F_\mu$, $F_\nu$ be their cumulative distribution ...
mnmn1993's user avatar
2 votes
0 answers
77 views

Can we control the Wasserstein metric between $\mu$ and $\nu$ by their moment difference?

Fix $p \in [1, \infty)$. Let $(\mathcal P_p(\mathbb R^d), W_p)$ be the Wasserstein space of all Borel probability measures on $\mathbb R^d$ with finite $p$-th moment. Let $D_p$ be the collection of ...
Analyst's user avatar
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0 votes
1 answer
121 views

Some continuity issues of the optimal transport map (Brenier map)

Let $\mu$ and $\nu$ be two probability measures with finite moments (in $\mathcal{P}_2(\mathbb{R})$) equipped with 2-Wasserstein distance. Let $F_\mu$, $F_\nu$ be their cumulative distribution ...
mnmn1993's user avatar
2 votes
0 answers
49 views

Instances of c-concavity outside of optimal transport?

Let $X$ and $Y$ be metric spaces, and let $c:X\times Y\rightarrow \mathbb{R}$ be a nonnegative function which we refer to as a cost. For any $\phi:X\rightarrow \mathbb{R}$ and $\psi:Y\rightarrow \...
Brendan Mallery's user avatar
4 votes
0 answers
95 views

Exponential map for tangent space of space of distributions $\mathscr{P}_2(X)$

In Chapter 8 of the book Gradient Flows In Metric Spaces and in the Space of Probability Measures by Ambrosio et al., the tangent space to the space of distributions on $X$ (let's say $X=\mathbb{R}^d$)...
Juno Kim's user avatar
3 votes
0 answers
125 views

On the continuity with respect to the increasing convex order

For $p\ge 1$, let $\mathcal P_p(\mathbb R)$ be the set of probability measures on $\mathbb R$ of finite $p^{\rm th}$ moment. Denote by $W_p$ the Wasserstein metric of order $p$ and by $\preceq$ the ...
Fawen90's user avatar
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3 votes
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Continuous trajectory of midpoints of length-minimizing geodesics

Let $M$ be a smooth Riemannian manifold, $x$ be a point in $M$, and $\lambda:[0,1]\to M$ be a continuous path. Can we find a family of length-minimizing constant speed geodesics $\gamma_t:[0,1]\to M$ ...
Cave Johnson's user avatar
1 vote
1 answer
81 views

Is it true that $\xi \in \partial G (v)$ implies $\frac{\xi}{F'(\phi (v))} \in \partial \phi (v)$?

I am reading the introduction of Chapter 10 in the book Gradient Flows by Ambrosio and his coauthors. As we have seen in Section 1.4, in the classical theory of subdifferential calculus for proper, ...
Akira's user avatar
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2 votes
1 answer
104 views

Gradient flows: evolution of geodesics

I’m trying to understand if, when I move the marginals of a Wasserstein geodesic along a contractive flow, the geodesic between the new probability measures is “near” to the geodesic connecting the ...
Ciccisio's user avatar
3 votes
0 answers
57 views

Convex combination of cyclically monotone sets

I want to show the following statement, but I am not sure how. Proposition(?): Let $C \in \mathbb{R}^d$ be a compact convex set, and let $u, v : C \to \mathbb{R}$ be smooth convex functions. Suppose $$...
Paruru's user avatar
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4 votes
1 answer
243 views

Perturbation of Wasserstein distance: looking for references

I am doing readings related to Optimal transport which is new to me and I often encounter the following statement regarding a sort of derivative of the Wasserstein distance: $u$ and $v$ be two ...
Guy Fsone's user avatar
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2 votes
0 answers
69 views

Construct a Bregman divergence from Wasserstein distance

I was wondering whether one has studied the Bregman divergence arising from a squared Wasserstein distance. More precisely, let $\Omega\subset \mathbb{R}^d$ be a compact set and $c\in \Omega\times \...
John's user avatar
  • 483
6 votes
2 answers
885 views

Weak convergence + convergence of the norm implies strong convergence in Orlicz spaces

It is known [1, proposition 3.32] and a classical trick in PDEs that, in any uniformly convex Banach space $X$, weak convergence $x_n\rightharpoonup x$ together with convergence of the norm $\|x_n\|_X\...
leo monsaingeon's user avatar
0 votes
1 answer
45 views

How is this interpolating curve well-defined in the minimizing movement scheme?

Let $\Omega$ be a compact domain of $\mathbb R^d$. Let $\mathcal P (\Omega)$ be the space of probability measures on $\Omega$. For each $\tau >0$, let $(\varrho^\tau_{(k)})_{k \in \mathbb N} \...
Akira's user avatar
  • 851
4 votes
2 answers
464 views

How to get this inequality in Santambrogio's book about optimal transport?

Let $\hat{\varrho}, \tilde{\varrho}$ be probability density functions on $\mathbb R^d$ where $\tilde{\varrho} \in L^{\infty} (\mathbb R^d)$. For $\varepsilon \in [0, 1]$, we define $\varrho_{\...
Akira's user avatar
  • 851
0 votes
1 answer
79 views

Can we lower bound this entropy by $\int_{\mathbb R^d} \rho^k (x) \, \mathrm d x$ and $\int_{\mathbb R^d} |x|^2\rho (x) \, \mathrm d x$?

We define $U : [0, \infty) \to [0, \infty)$ by $U(0) := 1$ and $U (s) := s \log s + (1-s)$ for $s >0$. Then $U$ is strictly convex. The minimum of $U$ is $0$ and is attained at $s=1$. Let $\mathcal ...
Akira's user avatar
  • 851
4 votes
2 answers
192 views

Are the sublevel sets of Boltzmann entropy compact in Wasserstein distance?

For Lebesgue-absolutely continuous probability measures $\rho\ll \mathcal{L}^d$ in the whole space $\mathbb{R}^d$ with finite second moments (i-e $\rho\in \mathcal{P}^2_{ac}(\mathbb{R}^d)$), let $$ \...
Akira's user avatar
  • 851
3 votes
1 answer
106 views

Let $\mu : [0, T] \to \mathcal P_2^a (\mathbb R^d), t \mapsto \mu_t$ be absolutely continuous. Is $t \mapsto \mathcal H (\mu_t)$ continuous?

We endow the space $\mathcal P_2^a (\mathbb R^d)$ of absolutely continuous probability measures with finite second moment with the Wasserstein distance $W_2$. Let $\mathcal H (\mu)$ be the relative ...
Akira's user avatar
  • 851
4 votes
0 answers
170 views

Compactness of the unit ball in the space of Radon measures w.r.t. the Kantorovich-Rubinstein norm

This question was posted previously but has not attracted any responses so I am repharising it in a slightly different language hoping to reach a wider community Let $(X,d)$ be a pointed metric space ...
Yury Korolev's user avatar
1 vote
1 answer
244 views

Continuity equation $\partial_t \mu_t+\operatorname{div} (v_t \mu_t)=0$: are these two notions of weak solution equivalent?

Let $\Omega$ be an open connected convex subset of $\mathbb R^d$. Let $\mathcal P (\Omega)$ be the space of Borel probability measures on $\Omega$. Let $C_0 (\Omega)$ be the space of real-valued ...
Analyst's user avatar
  • 647
3 votes
2 answers
639 views

Wasserstein distance between product measures

For two probability measures $\mu,\nu$ on $\mathbb{R}^n$, let $$W_p(\mu,\nu)^p=\inf_{\pi}\int\|x-y\|^p_2\ \pi(dx\ dy)$$ denote the $p^\text{th}$ Wasserstein distance between $\mu, \nu$, where the ...
Ribhu's user avatar
  • 311
1 vote
0 answers
133 views

Optimal transport-like problem where the objective depends on conditional probability distribution

$\DeclareMathOperator\marg{marg}$I would like to know if the following problem can be studied as an optimal transport problem, possibly imposing additional assumptions on the data. Consider two sets $\...
Francesco Bilotta's user avatar
1 vote
1 answer
206 views

What does $g_x^{-1}$ mean where $g$ is a Riemannian metric?

I am reading this paper about the Wasserstein-Fisher-Rao distance and they define the Wasserstein-Fisher-Rao distance on a manifold as follows (page 9): Here, $M$ is a compact Riemannian manifold, $\...
Kaira's user avatar
  • 237
2 votes
0 answers
80 views

relative entropy, Fisher information, and metric slope for non-convex domains

$\newcommand{\R}{\mathbb R}$ If $\Omega\subset \R^d$ is a convex domain it is well-known that the relative entropy $$ \mathcal H(\rho)= \int_{\Omega}\rho\log\rho \ \mathrm{d}x \qquad \mbox{for }\rho=...
leo monsaingeon's user avatar
1 vote
1 answer
290 views

Optimal transport between two matrices

I'm investigating the use of optimal transport to define a distance between non-negative matrices that satisfy the condition $\mathbf e^\top\mathbf M\mathbf e = 1$ (i.e., the sum of all elements in ...
Peyman's user avatar
  • 243
0 votes
1 answer
285 views

Derivative of Wasserstein distance $W^p_p$ along solutions of the continuity equation (contradicting statements in different sources)

Let $(\rho^{(i)}_t,{\bf v}^{(i)}_t)$ for $i = 1,2$ be two solutions of the continuity equation $$\partial \rho^{(i)}_t + \nabla\cdot \left({\bf v}^{(i)}_t \rho^{(i)}_t\right) = 0 \label{1}\tag{1}$$ on ...
Fei Cao's user avatar
  • 700
1 vote
1 answer
56 views

Generalised Lebesgue transform continuous wrt. strict topology?

Let $X$ and $Y$ be $\sigma$-compact spaces, and $\mu$ [resp. $\nu$] be a regular Borel probability measure on $X$ [resp. $Y$]. For a bounded continuous $c:X\times Y\rightarrow\mathbb{R}$, consider the ...
fsp-b's user avatar
  • 451
0 votes
1 answer
66 views

Continuity of generalised Legendre transform

Let $X$ and $Y$ be $\sigma$-compact spaces, and $\mu$ [resp. $\nu$] be a regular Borel probability measure on $X$ [resp. $Y$]. For a bounded continuous $c:X\times Y\rightarrow\mathbb{R}$, we consider ...
fsp-b's user avatar
  • 451
2 votes
0 answers
46 views

$\sigma$-compactness of probability measures under a refined topology

Denote Polish spaces $(X, \tau_x)$ and $(Y, \tau_y)$, where $X$ and $Y$ are closed subsets of $\mathbb{R}$. Consider a Borel measurable function $f: (X \times Y, \tau_x \times \tau_y) \rightarrow \...
Hans's user avatar
  • 195
0 votes
0 answers
58 views

An optimization problem defined by optimal transportation

Let $\mu,\nu$ be two probability measures on $E:=\mathbb R^d$ and denote by $\gamma:=\mu\otimes \nu$ the product measure on $E\times E$. Define $\mathcal K$ to be the class of continuous functions $k:...
Fawen90's user avatar
  • 975
4 votes
0 answers
224 views

Weight transfer proof of Turán’s theorem

Turán’s theorem, which states that a $K_{p+1}$-free graph contains at most $(1-1/p)\frac{N^2}{2}$ edges, can be proven in many different ways, as pointed out, for example in M. Aigner, G. M. Ziegler, ...
Martin Leshko's user avatar
7 votes
1 answer
281 views

Local Lipschitzness of parameterization of Gaussians in Wasserstein space

Fix a positive integer $n$ and consider the $2$-Wasserstein space $\mathcal{P}_2(\mathbb{R}^n)$. Let $X$ be the cone of $n\times n$ symmetric positive semidefinite matrices with Frobenius norm and ...
Justin_other_PhD's user avatar
0 votes
0 answers
24 views

Max diameter of random partition arising from optimal transport

Let $\mathbf S^2\subset \mathbb R^3$ be the sphere centered at the origin with radius chosen such that $m(\mathbf S^2)=n$, where $m$ denotes the surface area measure. Consider the Wasserstein distance ...
Fawen90's user avatar
  • 975
5 votes
0 answers
139 views

Log Sobolev inequality uniform in parameters

Fix a positive integer $N$. For $\theta \in [0,2\pi]$, set $\sigma_k(\theta) :=(\cos(k\theta),\sin(k\theta)) \in S^1$ for each integer $1\leq k\leq N$. Now for vectors $x_1,\ldots,x_N\in \mathbb{R}^2$,...
Matt Rosenzweig's user avatar
4 votes
0 answers
193 views

Schrödinger Bridge for other costs

Stochastic control formulations of the Schrödinger bridge problem between $\mu,\nu$ are well known (e.g Chen et al Eq. 4.23) $$\inf \limits_{p_t, v_t} \int_0^T \int \frac{1}{2}\lvert v_t\rvert^2 p_t ...
nico's user avatar
  • 91
2 votes
1 answer
78 views

A variant of (discrete) optimal transport problem

Let $\alpha=(\alpha_1,\ldots,\alpha_m)\subset\mathbb R^m_+$ and $\beta=(\beta_1,\ldots,\beta_n)\subset\mathbb R^n_+$ be given and satisfy $$\sum_{i=1}^m \alpha_i =1 = \sum_{j=1}^n\beta_j.$$ Define $\...
Fawen90's user avatar
  • 975
1 vote
0 answers
82 views

Representation formula for the continuity equation on a separable Hilbert space

The following is an informal question for which I'd like to (ideally) find a reference. I'm quite a novice in this area but would be happy to find a reference to a theorem along the following lines (...
Gregor Samsa's user avatar
2 votes
0 answers
110 views

Approximating solutions to Monge-Ampere from optimal transport plans

I am interested in finding numerical solutions to a Monge-Ampere type equation for applications in physics. Due to the close connection between Monge-Ampere and optimal transport and the well ...
Yly's user avatar
  • 946
3 votes
2 answers
187 views

Getting Wasserstein closeness from a derivative estimate

In my setting, $\mu$ and $\nu$ are probability measures on $\mathbb{R}^{2}$ with compact support. For any function $f\in{C^{2}_{b}(\mathbb{R}^{2})}$, I have the estimate: $$ |\mathbb{E}_{\mu}(f)-\...
David Pechersky's user avatar
3 votes
1 answer
138 views

Is this map (from the space of probability densities to the Wasserstein space) Lipschitz?

Let $p \in [1, \infty)$. Let $\mathcal P_p(\mathbb R^d)$ be the space of all Borel probability measures on $\mathbb R^d$ with finite $p$-th moments. Let $D_p$ be the collection of all Borel measurable ...
Analyst's user avatar
  • 647
1 vote
1 answer
228 views

Is the Wasserstein distance to the empirical measure minimized by the underlying distribution?

Let $S$ be a metric space and denote the set of probability measures on $S$ by $\mathcal{P}(S)$. Fix $\mu\in \mathcal{P}(S)$ and denote the law of $N\geq 1$ i.i.d samples $X=(X_1,\ldots,X_N)$ from $\...
joemrt's user avatar
  • 53
4 votes
1 answer
118 views

Riemannian submanifolds of $2$-Wasserstein space

In the article "Wasserstein Geometry Of Gaussian Measures" by Asuka Takatsu the author shows how the space of d-dimensional Gaussian probability measures with non-singular covariance ...
Annie's user avatar
  • 91
8 votes
1 answer
323 views

Mass transportation proof of the Gaussian isoperimetric inequality?

In his book "Topics in optimal transportation", Graduate Studies in Mathematics 58, AMS 2003, Villani presents a proof, due to Gromov, of the classical isoperimetric inequality in Euclidean ...
Xiazhong Zhu's user avatar
0 votes
0 answers
107 views

Wasserstein compactness of sublevel sets of relative entropy

Let $\mathcal{P}({\mathbb{R}^d})$ denote the set of Borel probability measures on $\mathbb{R}^d$, and let $\pi \in \mathcal{P} (\mathbb{R}^d)$. It is known that the sets $\{ \mu \in \mathcal{P}(\...
pseudocydonia's user avatar
1 vote
0 answers
168 views

$L^2$ metric on $\textrm{Diff}(M)$ and geodesics

The paper Geometry of diffeomorphism groups, complete integrability and optimal transport mentions the following: The group $\textrm{Diff}(M)$ carries a natural $L^2$-metric $\displaystyle \langle\...
Kaira's user avatar
  • 237
2 votes
1 answer
194 views

For diffeomorphism $f$, if $X$ and $f(X)$ are both Gaussian, then $f$ is affine

I am trying to prove the following. Let $f:\mathbb{R}^{n}\to \mathbb{R}^n$ be a diffeomorphism. If $X$ and $f(X)$ are both $n$ -dimensional Gaussian variables, then $f$ is affine. That is, there ...
Kaira's user avatar
  • 237
1 vote
0 answers
59 views

Lipschitzness of conditional law of a stochastic filtering problem wrt the Wasserstein distance

Let $(X_t)_{t\ge 0}$ and $(Y_t)_{t\ge 0}$ be a pair of stochastic processes taking values in $\mathbb{R}^n$ and in $\mathbb{R}^m$; defined on a filtered probability spaces $(\Omega,\mathcal{F},(\...
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