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Efficient Continual Finite-Sum Minimization

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Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Contextual Stochastic Bilevel Optimization

Daniel Kuhn, Andreas Krause, Yifan Hu, Jie Wang

We introduce contextual stochastic bilevel optimization (CSBO) -- a stochastic bilevel optimization framework with the lower-level problem minimizing an expectation conditioned on some contextual information and the upper-level decision variable. This fram ...

2023

Efficient approximation of cardiac mechanics through reduced-order modeling with deep learning-based operator approximation

Alfio Quarteroni, Andrea Manzoni

Reducing the computational time required by high-fidelity, full-order models (FOMs) for the solution of problems in cardiac mechanics is crucial to allow the translation of patient-specific simulations into clinical practice. Indeed, while FOMs, such as th ...

Hoboken2023

Tensor-Based Numerical Method For Stochastic Homogenization

This paper addresses the complexity reduction of stochastic homogenization of a class of random materials for a stationary diffusion equation. A cost-efficient approximation of the correctors is obtained using a method designed to exploit quasi-periodicity ...

SIAM PUBLICATIONS2022

Distributed Design for Decentralized Control using Chordal Decomposition and ADMM

Maryam Kamgarpour

We propose a distributed design method for decentralized control by exploiting the underlying sparsity properties of the problem. Our method is based on chordal decomposition of sparse block matrices and the alternating direction method of multipliers (ADM ...

2020

RBF Based CWENO Method

Jan Sickmann Hesthaven, Fabian Mönkeberg

Solving hyperbolic conservation laws on general grids can be important to reduce the computational complexity and increase accuracy in many applications. However, the use of non-uniform grids can introduce challenges when using high-order methods. We propo ...

2018

An FFT-based Numerical Method for Elasto-Plastic Contact

Jean-François Molinari, Guillaume Anciaux, Lucas Henri Galilée Frérot

Contact of rough surfaces is of prime importance in the study of friction and wear. Numerical simulations are well suited for this non-linear problem, but natural surfaces being fractal [1], they have high discretization requirements. There is therefore a ...

2018

, , ,

The optimal power-flow problem (OPF) has always played a key role in the planning and operation of power systems. Due to the non-linear nature of the AC power-flow equations, the OPF problem is known to be non-convex, therefore hard to solve. During the la ...

Elsevier2017

Multi-index Stochastic Collocation for random PDEs

Fabio Nobile, Lorenzo Tamellini

In this work we introduce the Multi-Index Stochastic Collocation method (MISC) for computing statistics of the solution of a PDE with random data. MISC is a combination technique based on mixed differences of spatial approximations and quadratures over the ...

2016

MATHICSE Technical Report : Multi-index stochastic collocation for random PDEs

Fabio Nobile, Lorenzo Tamellini

MATHICSE2015