BluePyOpt: Leveraging Open Source Software and Cloud Infrastructure to Optimise Model Parameters in Neuroscience

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Coherent Diffraction Imaging (CDI) is an experimental technique to image isolated structures by recording the scattered light. The sample density can be recovered from the scattered field through a Fourier Transform operation. However, the phase of the fie ...

This work aims to develop a scalable surrogate modelling framework for robust multidisciplinary design optimisation (RMDO) in complex engineering systems. Focusing on gas-bearing supported rotors, it addresses the need to maintain system performance under ...

In this work, we develop first-order (Hessian-free) and zeroth-order (derivative-free) implementations of the Cubically Regularized Newton Method for solving general non-convex optimization problems. For that, we employ finite difference approximations of ...

Integer linear programming (ILP) is an elegant approach to solve linear optimization problems, naturally described using integer decision variables. Within the context of physics-inspired machine learning (ML) applied to chemistry, we demonstrate the relev ...

Energy efficiency is crucial for the sustainable operation of industrial and urban sectors. However, practicing engineers seldom have access to open-source tools that can readily evaluate and compare scenarios. In this work, a novel web-based tool called R ...

This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehicles (e-ADARPs). The scheduling heuristic, based on linear programming theor ...

Time-domain solutions of Maxwell’s equations in homogeneous and isotropic media are paramount to studying transient or broadband phenomena. However, analytical solutions are generally unavailable for practical applications, while numerical solutions are co ...

In algorithms for solving optimization problems constrained to a smooth manifold, retractions are a well-established tool to ensure that the iterates stay on the manifold. More recently, it has been demonstrated that retractions are a useful concept for ot ...

vanishing viscosity, networks. This work has received funding from the Alexander von Humboldt-Professorship program, the Transregio 154 Project "Mathematical Modelling, Simulation and Optimization Using the Example of Gas Networks" of the DFG, the grant PI ...

Predicting the evolution of systems with spatio-temporal dynamics in response to external stimuli is essential for scientific progress. Traditional equations-based approaches leverage first principles through the numerical approximation of differential equ ...

Literature on linear induction motors (LIMs) has proposed several approaches to model the behavior of such devices for different applications. In terms of accuracy and fidelity, field analysis-based models are the most relevant. Closed-form or numerical so ...

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

This directory contains open-source data and code obtained at the UNFoLD laboratory at EPFL. This code implements a new tracking method for fast deformation of flapping flags using an event-based camera. Sampled data from experimental results as well as si ...

The goal of this work is to use anisotropic adaptive finite elements for the numerical simulation of aluminium electrolysis. The anisotropic adaptive criteria are based on a posteriori error estimates derived for simplified problems. First, we consider an ...

The method of moments (MOM), as introduced by Roger F. Harrington more than 50 years ago, is reviewed in the context of the classic potential integral equation (IE) formulations applied to both electrostatic (part 1) and electrodynamic or full-wave problem ...

The method of moments (MOM), as introduced by R. F. Harrington more than 50 years ago, is reviewed in the context of the classic potential integral equation (PIE) formulations applied to both electrostatic (part 1) and electrodynamic, or full-wave, problem ...

Multiple tensor-times-matrix (Multi-TTM) is a key computation in algorithms for computing and operating with the Tucker tensor decomposition, which is frequently used in multidimensional data analysis. We establish communication lower bounds that determine ...

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 ...

In this thesis we study stability from several viewpoints. After covering the practical importance, the rich history and the ever-growing list of manifestations of stability, we study the following. (i) (Statistical identification of stable dynamical syste ...

Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy a desired objective under minimal calls to oracles (computational property predictors). This problem becomes more apparen ...

BluePyOpt: Leveraging Open Source Software and Cloud Infrastructure to Optimise Model Parameters in Neuroscience

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SPRING, an effective and reliable framework for image reconstruction in single-particle Coherent Diffraction Imaging

Dimensionless Group-Driven Ensemble Neural Networks for Robust Design Optimisation in Engineering

First and Zeroth-Order Implementations of the Regularized Newton Method with Lazy Approximated Hessians

Integer Linear Programming for Unsupervised Training Set Selection in Molecular Machine Learning

ROSMOSE: A web-based decision support tool for the design and optimization of industrial and urban energy systems

A ride time-oriented scheduling algorithm for dial-a-ride problems

The time-domain Cartesian multipole expansion of electromagnetic fields

From low-rank retractions to dynamical low-rank approximation and back

CONTROL OF HYPERBOLIC AND PARABOLIC EQUATIONS ON NETWORKS AND SINGULAR LIMITS

Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks

Pseudo-Three-Dimensional Analytical Model of Linear Induction Motors for High-Speed Applications

Reliable data-driven decision-making through optimal transport

Data from: Event-based reconstruction of time-resolved centreline deformation of flapping flags

Adaptive Finite Elements with Large Aspect Ratio. Application to Aluminium Electrolysis

Roger F. Harrington and the Method of Moments: Part 2: Electrodynamics

Roger F. Harrington and the Method of Moments: Part 1: Electrostatics

COMMUNICATION LOWER BOUNDS AND OPTIMAL ALGORITHMS FOR MULTIPLE TENSOR-TIMES-MATRIX COMPUTATION

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

Stability: a search for structure

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning