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The goal of causal mediation analysis, often described within the potential outcomes framework, is to decompose the effect of an exposure on an outcome of interest along different causal pathways. Using the assumption of sequential…

Methodology · Statistics 2021-11-09 Lexi Rene , Antonio R. Linero , Elizabeth Slate

We extend the non-parametric framework of reaction coordinate optimization to non-equilibrium ensembles of (short) trajectories. For example, we show how, starting from such an ensemble, one can obtain an equilibrium free energy profile…

Chemical Physics · Physics 2021-02-09 Sergei V. Krivov

Generally, multi-objective optimisation problems are solved exactly or approximated by solving a series of scalarisations, for example by dichotomic search. In this paper, we take a different approach and attempt to compute the set of all…

Optimization and Control · Mathematics 2026-01-28 Oliver Bachtler , Felix Fritz , Stefan Ruzika

The path-specific effect (PSE) is of primary interest in mediation analysis when multiple intermediate variables between treatment and outcome are observed, as it can isolate the specific effect through each mediator, thus mitigating…

Methodology · Statistics 2025-07-16 Jiawei Shan , Ting Wang , Wei Li , Chunrong Ai

The coating design for mirrors used in interferometric detectors of gravitational waves currently consists of stacks of two alternating dielectric materials with different refractive indexes. In order to explore the performance limits of…

Instrumentation and Methods for Astrophysics · Physics 2019-07-30 V. Pierro , V. Fiumara , F. Chiadini , F. Bobba , G. Carapella , C. Di Giorgio , O. Durante , R. Fittipaldi , E. Mejuto Villa , J. Neilson , M. Principe , I. M. Pinto

This paper proposes a fully distributed reactive power optimization algorithm that can obtain the global optimum of non-convex problems for distribution networks without a central coordinator. Second-order cone (SOC) relaxation is used to…

Optimization and Control · Mathematics 2014-09-12 Weiye Zheng , Wenchuan Wu , Boming Zhang , Hongbin Sun , Liu Yibing

Estimating direct and indirect causal effects from observational data is crucial to understanding the causal mechanisms and predicting the behaviour under different interventions. Causal mediation analysis is a method that is often used to…

Machine Learning · Computer Science 2023-12-19 Ziqi Xu , Debo Cheng , Jiuyong Li , Jixue Liu , Lin Liu , Ke Wang

We develop a reduced-order framework for optimizing mixing in two-dimensional incompressible flows. Instead of optimizing the full transport PDE, the method maximizes the length of advected material interfaces, leading to a…

Numerical Analysis · Mathematics 2026-05-07 Ziqian Li , Enrique Zuazua

A deep equilibrium model (DEQ) is implicitly defined through an equilibrium point of an infinite-depth weight-tied model with an input-injection. Instead of infinite computations, it solves an equilibrium point directly with root-finding…

Machine Learning · Computer Science 2023-03-30 Zenan Ling , Xingyu Xie , Qiuhao Wang , Zongpeng Zhang , Zhouchen Lin

In this paper we consider multi-objective optimization problems over a box. The problem is very relevant and several computational approaches have been proposed in the literature. They broadly fall into two main classes: evolutionary…

Optimization and Control · Mathematics 2022-12-08 Matteo Lapucci , Pierluigi Mansueto , Fabio Schoen

The paper investigates the weighted sum-rate maximization (WSRM) problem with latent interfering sources outside the known network, whose power allocation policy is hidden from and uncontrollable to optimization. The paper extends the…

Information Theory · Computer Science 2023-01-25 Lei You

We consider adaptive finite element methods for second-order elliptic PDEs, where the arising discrete systems are not solved exactly. For contractive iterative solvers, we formulate an adaptive algorithm which monitors and steers the…

Numerical Analysis · Mathematics 2021-07-14 Gregor Gantner , Alexander Haberl , Dirk Praetorius , Stefan Schimanko

A key challenge in estimating causal effects from observational data is handling confounding and is commonly achieved through weighting methods that balance distribution of covariates between treatment and control groups. Weighting…

Methodology · Statistics 2025-12-23 Simion De , Jared D. Huling

Mediation analytics help examine if and how an intermediate variable mediates the influence of an exposure variable on an outcome of interest. Quantiles, rather than the mean, of an outcome are scientifically relevant to the comparison…

Methodology · Statistics 2024-12-23 Canyi Chen , Yinqiu He , Huixia J. Wang , Gongjun Xu , Peter X. -K. Song

In this paper, we propose an operator-inference-based reduction approach for contact problems, leveraging snapshots from simulations without active contact. Contact problems are solved using adjoint methods, by switching to the dual system,…

Numerical Analysis · Mathematics 2025-05-26 Diana Manvelyan-Stroot , Yevgeniya Filanova , Igor Pontes Duff , Peter Benner , Utz Wever

Many phenomena in real world social networks are interpreted as spread of influence between activated and non-activated network elements. These phenomena are formulated by combinatorial graphs, where vertices represent the elements and…

Discrete Mathematics · Computer Science 2024-03-01 Siavash Askari , Manouchehr Zaker

We consider the problem of identifying intermediate variables (or mediators) that regulate the effect of a treatment on a response variable. While there has been significant research on this classical topic, little work has been done when…

Methodology · Statistics 2021-07-29 Abhishek Chakrabortty , Preetam Nandy , Hongzhe Li

We explore a scenario where Dark Matter (DM) couples to the Standard Model mainly via a scalar mediator ${\cal S}$ that is odd under a $Z_2$ symmetry, leading to interesting collider signatures. In fact, if linear interactions with the…

High Energy Physics - Phenomenology · Physics 2020-01-08 Florian Goertz , Karla Tame-Narvaez , Valentin Tenorth

For effective decision support in scenarios with conflicting objectives, sets of potentially optimal solutions can be presented to the decision maker. We explore both what policies these sets should contain and how such sets can be computed…

Artificial Intelligence · Computer Science 2023-07-19 Willem Röpke , Conor F. Hayes , Patrick Mannion , Enda Howley , Ann Nowé , Diederik M. Roijers

The large-scale multiple testing inherent to high throughput biological data necessitates very high statistical stringency and thus true effects in data are difficult to detect unless they have high effect sizes. One solution to this…

Methodology · Statistics 2017-12-21 Mohamad S. Hasan