Publications associées à Méthode de Condorcet

Computational conceptual design — typological exploration of spatial truss systems through optimization

Corentin Jean Dominique Fivet, Jonas Warmuth, Pierluigi D'Acunto

Exploring a wide range of design options is crucial for every sound conceptual design process. In the conventional structural design workflow, optimization techniques are generally employed to generate well-performing design options. However, focusing only ...

International Association for Shell and Spatial Structures (IASS)2023

Incompleteness of graph neural networks for points clouds in three dimensions

Michele Ceriotti, Sergey Pozdnyakov

Graph neural networks (GNN) are very popular methods in machine learning and have been applied very successfully to the prediction of the properties of molecules and materials. First-order GNNs are well known to be incomplete, i.e. there exist graphs that ...

IOP Publishing Ltd2022

The probability of intransitivity in dice and close elections

Jan Hazla

We study the phenomenon of intransitivity in models of dice and voting. First, we follow a recent thread of research for n-sided dice with pairwise ordering induced by the probability, relative to 1/2, that a throw from one die is higher than the other. We ...

2020

Synthesis and chemical transformations of diazolyl alpha,alpha-difluoroacetates

Pavlo Khodakivskyi

Optimized protocols for the synthesis of diazolyl alpha,alpha-difluoroacetates via deoxofluorination of the corresponding glyoxylates with Morph-DAST are described. The method allowed the preparation of the title fluoridated building blocks in 73-96 % yiel ...

ELSEVIER SCIENCE SA2020

Monotonic Prefix Consistency in Distributed Systems

Rachid Guerraoui, Dragos-Adrian Seredinschi, Jad Hamza

We study the issue of data consistency in distributed systems. Specifically, we consider a distributed system that replicates its data at multiple sites, which is prone to partitions, and which is assumed to be available (in the sense that queries are alwa ...

2018

Applications of Approximate Learning and Inference for Probabilistic Models

Young Jun Ko

We develop approximate inference and learning methods for facilitating the use of probabilistic modeling techniques motivated by applications in two different areas. First, we consider the ill-posed inverse problem of recovering an image from an underdeter ...

EPFL2017

Automated Reconstruction of Evolving Curvilinear Tree Structures

Przemyslaw Rafal Glowacki

Curvilinear networks are prevalent in nature and span many different scales, ranging from micron-scale neural structures in the brain to petameter-scale dark-matter arbors binding massive galaxy clusters. Reliably reconstructing them in an automated fashio ...

EPFL2016

How to Benchmark Objective Quality Metrics from Paired Comparison Data?

Touradj Ebrahimi, Philippe Hanhart

The procedures commonly used to evaluate the performance of objective quality metrics rely on ground truth mean opinion scores and associated confidence intervals, which are usually obtained via direct scaling methods. However, indirect scaling methods, su ...

Ieee2016

Online Collaborative Prediction of Regional Vote Results

Patrick Thiran, Matthias Grossglauser, Mohammad Emtiyaz Khan, Vincent Etter

We consider online predictions of vote results, where regions across a country vote on an issue under discussion. Such online predictions before and during the day of the vote are useful to media agencies, polling institutes, and political parties, e.g., t ...

IEEE2016

Integration of scientific and social networks

Ehsaneddin Asgari

In this paper, we address the problem of scientific-social network integration to find a matching relationship between members of these networks (i.e. The DBLP publication network and the Twitter social network). This task is a crucial step toward building ...

Springer2014