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A general class of nonconvex optimization problems is considered, where the penalty is the composition of a linear operator with a nonsmooth nonconvex mapping, which is concave on the positive real line. The necessary optimality condition…

Optimization and Control · Mathematics 2018-04-23 Daria Ghilli , Karl Kunisch

An algorithm is proposed for generalized mean curvature flow of closed two-dimensional surfaces, which include inverse mean curvature flow, powers of mean and inverse mean curvature flow, etc. Error estimates are proven for semi- and full…

Numerical Analysis · Mathematics 2021-03-16 Tim Binz , Balázs Kovács

Estimating the impact of environmental processes on vertical reef development in geological time is a very challenging task. pyReef-Core is a deterministic carbonate stratigraphic forward model designed to simulate the key biological and…

Coastal erosion describes the displacement of land caused by destructive sea waves, currents or tides. Major efforts have been made to mitigate these effects using groins, breakwaters and various other structures. We try to address this…

Optimization and Control · Mathematics 2022-09-16 Luka Schlegel , Volker Schulz

This paper presents a survey of ocean simulation and rendering methods in computer graphics. To model and animate the ocean's surface, these methods mainly rely on two main approaches: on the one hand, those which approximate ocean dynamics…

We study the geometric flow of a planar curve driven by its curvature and the normal derivative of its capacity potential. Under a convexity condition that is natural to our problem, we establish long term existence and large time…

Analysis of PDEs · Mathematics 2017-10-16 Luis Caffarelli , Hui Yu

Beginning with the projectively invariant method for linear programming, interior point methods have led to powerful algorithms for many difficult computing problems, in combinatorial optimization, logic, number theory and non-convex…

Numerical Analysis · Computer Science 2014-12-11 Narendra Karmarkar

Forward and inverse models are used throughout different engineering fields to predict and understand the behaviour of systems and to find parameters from a set of observations. These models use root-finding and minimisation techniques…

Computational Engineering, Finance, and Science · Computer Science 2023-08-08 Preslav Aleksandrov

Climate models are essential to understand and project climate change, yet long-standing biases and uncertainties in their projections remain. This is largely associated with the representation of subgrid-scale processes, particularly…

The design of adaptive structures is one method to improve sustainability of buildings. Adaptive structures are able to adapt to different loading and environmental conditions or to changing requirements by either small or large shape…

Computational Engineering, Finance, and Science · Computer Science 2020-12-08 Renate Sachse , Florian Geiger , Manfred Bischoff

We define objective Eulerian Coherent Structures (OECSs) in two-dimensional, non-autonomous dynamical systems as instantaneously most influential material curves. Specifically, OECSs are stationary curves of the averaged instantaneous…

Dynamical Systems · Mathematics 2016-06-22 Mattia Serra , George Haller

Condensable species are crucial in shaping planetary climate. A wide range of planetary climate systems involve understanding non-dilute condensable substances and their influence on climate dynamics. There has been progress on large-scale…

Earth and Planetary Astrophysics · Physics 2021-12-22 Xianyu Tan , Maxence Lefevre , Raymond Pierrehumbert

This paper studies system theoretic properties of the class of difference inclusions of convex processes. We will develop a framework considering eigenvalues and eigenvectors, weakly and strongly invariant cones, and a decomposition of…

Optimization and Control · Mathematics 2021-12-30 Jaap Eising , M. Kanat Camlibel

The impact of environmental variability on population size growth rate in dynamic models is a recurrent issue in the theoretical ecology literature. In the scalar case, R. Lande pointed out that results are ambiguous depending on whether…

Probability · Mathematics 2009-08-19 Michel De Lara

Causal structures give us a way to understand the origin of observed correlations. These were developed for classical scenarios, but quantum mechanical experiments necessitate their generalisation. Here we study causal structures in a broad…

Quantum Physics · Physics 2021-06-30 Mirjam Weilenmann , Roger Colbeck

We consider high-dimensional estimation problems where the number of parameters diverges with the sample size. General conditions are established for consistency, uniqueness, and asymptotic normality in both unpenalized and penalized…

Statistics Theory · Mathematics 2025-04-08 Jana Gauss , Thomas Nagler

The push-forward operation enables one to redistribute a probability measure through a deterministic map. It plays a key role in statistics and optimization: many learning problems (notably from optimal transport, generative modeling, and…

Machine Learning · Statistics 2025-05-19 Lucas de Lara , Mathis Deronzier , Alberto González-Sanz , Virgile Foy

We establish upper bounds for the expected excess risk of models trained by proper iterative algorithms which approximate the local minima. Unlike the results built upon the strong globally strongly convexity or global growth conditions…

Machine Learning · Computer Science 2022-10-11 Mingyang Yi , Ruoyu Wang , Zhi-Ming Ma

Control systems should enforce a desired property for both expected modeled situations as well as unexpected unmodeled environmental situations. Existing methods focus on designing controllers to enforce the desired property only when the…

Systems and Control · Electrical Eng. & Systems 2021-10-19 Rômulo Meira-Góes , Eunsuk Kang , Stéphane Lafortune , Stavros Tripakis

A recent literature considers causal inference using noisy proxies for unobserved confounding factors. The proxies are divided into two sets that are independent conditional on the confounders. One set of proxies are `negative control…

Econometrics · Economics 2021-10-11 Ben Deaner