Artificial Intelligence (AI) applications are being used to predict and assess behaviour in multiple domains, such as criminal justice and consumer f…

We develop a theoretical framework for the analysis of stabilized cut finite element methods for the Laplace-Beltrami operator on a manifold embedded…

Causal inference with observational data can be performed under an assumption of no unobserved confounders (unconfoundedness assumption). There is, h…

We present a continuous/discontinuous Galerkin method for approximating solutions to a fourth order elliptic PDE on a surface embedded in $\mathbb{R}…

Comprehending complex systems by simplifying and highlighting important dynamical patterns requires modeling and mapping higher-order network flows. …

To better understand the flows of ideas or information through social and biological systems, researchers develop maps that reveal important patterns…

Wide field-of-view imaging of fast processes in a microscope requires high light intensities motivating the use of lasers as light sources. However, …

We present novel geometric numerical integrators for Hunter--Saxton-like equations by means of new multi-symplectic formulations and known Hamiltonia…

This article presents explicit exponential integrators for stochastic Maxwell's equations driven by both multiplicative and additive noises. By utili…

The deployment of machine learning algorithms on resource-constrained edge devices is an important challenge from both theoretical and applied points…

When estimating the treatment effect in an observational study, we use a semiparametric locally efficient dimension reduction approach to assess both…

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Causal inference with observational longitudinal data and time-varying exposures is often complicated by time-dependent confounding and attrition. G-…

When using Convolutional Neural Networks (CNNs) for segmentation of organs and lesions in medical images, the conventional approach is to work with i…

Causal effect estimation tasks from observational data need to consider confounders of the causal relation of interest for controlling for (conditioning on). However, it is not necessary that all of them are considered but a ”sufficient” subset of t…

Conditioning on some set of confounders that causally affect both treatment and outcome variables can be sufficient for eliminating bias introduced b…

The purpose of this study is to investigate a method, using simulations, to improve contrast agent quantification in Dynamic Contrast Enhanced MRI. B…

We derive a new stabilized symmetric Nitsche method for enforcement of Dirichlet boundary conditions for elliptic problems of second order in cut iso…

In the causal inference literature a class of semi-parametric estimators are called robust if the estimator has desirable properties under the assump…

Grip control during robotic in-hand manipulation is usually modeled as part of a monolithic task, relying on complex controllers specialized for spec…

We present a cut finite element method for shape optimization in the case of linear elasticity. The elastic domain is defined by a level-set function…

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