Carla Tameling
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View article: Distribution of Distances based Object Matching: Asymptotic Inference
Distribution of Distances based Object Matching: Asymptotic Inference Open
In this article, we aim to provide a statistical theory for object matching based on a lower bound of the Gromov-Wasserstein distance related to the distribution of (pairwise) distances of the considered objects. To this end, we model gene…
View article: Colocalization for super-resolution microscopy via optimal transport
Colocalization for super-resolution microscopy via optimal transport Open
Super-resolution fluorescence microscopy is a widely used technique in cell biology. Stimulated emission depletion (STED) microscopy enables the recording of multiple-color images with subdiffraction resolution. The enhanced resolution lea…
View article: Simluated and real data
Simluated and real data Open
This are all real and simulated data set for the paper Colocalization for Super-Resolution Microscopy via Optimal Transport by Tameling et al.
View article: Simluated and real data
Simluated and real data Open
This are all real and simulated data set for the paper Colocalization for Super-Resolution Microscopy via Optimal Transport by Tameling et al.
View article: ctameling/OTC: Optimal Transport Colocalization
ctameling/OTC: Optimal Transport Colocalization Open
This is the version of the Code for publication of the paper Colocalization for Super-Resolution Microscopy via Optimal Transport by Tameling et al.
View article: Convex Relaxation of Discrete Vector-Valued Optimization Problems
Convex Relaxation of Discrete Vector-Valued Optimization Problems Open
We consider a class of infinite-dimensional optimization problems in which a\ndistributed vector-valued variable should pointwise almost everywhere take\nvalues from a given finite set $\\mathcal{M}\\subset\\mathbb{R}^m$. Such hybrid\ndisc…
View article: Gromov-Wasserstein Distance based Object Matching: Asymptotic Inference
Gromov-Wasserstein Distance based Object Matching: Asymptotic Inference Open
In this paper, we aim to provide a statistical theory for object matching based on the Gromov-Wasserstein distance. To this end, we model general objects as metric measure spaces. Based on this, we propose a simple and efficiently computab…
View article: Empirical Regularized Optimal Transport: Statistical Theory and Applications
Empirical Regularized Optimal Transport: Statistical Theory and Applications Open
We derive limit distributions for certain empirical regularized optimal transport distances between probability distributions supported on a finite metric space and show consistency of the (naive) bootstrap. In particular, we prove that th…
View article: Empirical optimal transport on countable metric spaces: Distributional limits and statistical applications
Empirical optimal transport on countable metric spaces: Distributional limits and statistical applications Open
We derive distributional limits for empirical transport distances between probability measures supported on countable sets. Our approach is based on sensitivity analysis of optimal values of infinite dimensional mathematical programs and a…
View article: Empirical Optimal Transport on Discrete Spaces: Limit Theorems, Distributional Bounds and Applications
Empirical Optimal Transport on Discrete Spaces: Limit Theorems, Distributional Bounds and Applications Open
Optimal Transport and especially distances based on optimal transport are a widely applied tool in different mathematical disciplines. Among others it is used in probability theory to study for example limit laws or derive concentration in…
View article: COMPUTATIONAL STRATEGIES FOR STATISTICAL INFERENCE BASED ON EMPIRICAL OPTIMAL TRANSPORT
COMPUTATIONAL STRATEGIES FOR STATISTICAL INFERENCE BASED ON EMPIRICAL OPTIMAL TRANSPORT Open
In this paper we discuss some recent limit laws for empirical optimal transport distances from a simulation perspective. On discrete spaces, this requires to solve another optimal transport problem in each simulation step, which reveals si…