Concept

Fitness approximation

Related publications (24)

DiffAirfoil: An Efficient Novel Airfoil Sampler Based on Latent Space Diffusion Model for Aerodynamic Shape Optimization

Surrogate-based optimization is widely used for aerodynamic shape optimization, and its effectiveness depends on representative sampling of the design space. However, traditional sampling methods are hard-pressed to effectively sample high-dimensional desi ...

2024

Enriching the Computational Toolbox for Organocatalysis

Simone Gallarati

Organocatalysis has evolved significantly over the last decades, becoming a pillar of synthetic chemistry, but traditional theoretical approaches based on quantum mechanical computations to investigate reaction mechanisms and provide rationalizations of ca ...

EPFL2023

Genetic Algorithms for the Discovery of Homogeneous Catalysts

Rubén Laplaza Solanas, Anne-Clémence Corminboeuf, Puck Elisabeth van Gerwen, Alexandre Alain Schöpfer, Simone Gallarati

In this account, we discuss the use of genetic algorithms in the inverse design process of homogeneous catalysts for chemical transformations. We describe the main components of evolutionary experiments, specifically the nature of the fitness function to o ...

2023

Geometric and Learning Methods for Robots to Navigate in Human Crowds with Application to Smart Mobility Devices

David Julian Gonon

The thesis at hand is concerned with robots' navigation in human crowds. Specifically, methods are developed for planning a mobile robot's local motion between pedestrians, and they are evaluated in experiments where a robot interacts with real pedestrians ...

EPFL2023

A General Framework for Optimal Data-Driven Optimization

Daniel Kuhn, Tobias Sutter

We propose a statistically optimal approach to construct data-driven decisions for stochastic optimization problems. Fundamentally, a data-driven decision is simply a function that maps the available training data to a feasible action. It can always be exp ...

2021

Population pharmacokinetic model selection assisted by machine learning

Jan Sickmann Hesthaven, Nadia Terranova

A fit-for-purpose structural and statistical model is the first major requirement in population pharmacometric model development. In this manuscript we discuss how this complex and computationally intensive task could benefit from supervised machine learni ...

SPRINGER/PLENUM PUBLISHERS2021

Convergence without Convexity: Sampling, Optimization, and Games

Ya-Ping Hsieh

Many important problems in contemporary machine learning involve solving highly non- convex problems in sampling, optimization, or games. The absence of convexity poses significant challenges to convergence analysis of most training algorithms, and in some ...

EPFL2020

Wasserstein Distributionally Robust Learning

Soroosh Shafieezadeh Abadeh

Many decision problems in science, engineering, and economics are affected by uncertainty, which is typically modeled by a random variable governed by an unknown probability distribution. For many practical applications, the probability distribution is onl ...

EPFL2020

Structurally informed exploration of a grammar-based design space

Graphic statics provide a visual understanding of the relation between a structures’ shape and its efforts, a valuable quality in the field of structural conception. When combined to a shape grammar, the graphical method has proven to be a very powerful to ...

2018

The Seamless Peer and Cloud Evolution Framework

Dario Floreano, Joshua Evan Auerbach, Giovanni Iacca, Guillaume Paul Olivier Leclerc

Evolutionary algorithms are increasingly being applied to problems that are too computationally expensive to run on a single personal computer due to costly fitness function evaluations and/or large numbers of fitness evaluations. Here, we introduce the Se ...

ACM Press2016

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