Concept

Problèmes de Hilbert

Publications associées (99)

Complex Representation Learning with Graph Convolutional Networks for Knowledge Graph Alignment

Thanh Trung Huynh, Quoc Viet Hung Nguyen, Thành Tâm Nguyên

The task of discovering equivalent entities in knowledge graphs (KGs), so-called KG entity alignment, has drawn much attention to overcome the incompleteness problem of KGs. The majority of existing techniques learns the pointwise representations of entiti ...

London2023

Hands-on tasks make learning visible: a learning analytics lens on the development of mechanistic problem-solving expertise in makerspaces

Richard Lee Davis, Bertrand Roland Schneider

This study investigated the impact of participating in a year-long digital-fabrication course on high-school seniors' problem-solving skills, with a focus on problems involving mechanistic systems. The research questions centered on whether working in a ma ...

New York2023

Mean Field Type Control With Species Dependent Dynamics via Structured Tensor Optimization

Isabel Haasler, Axel Ringh, Yiqiang Chen

In this letter we consider mean field type control problems with multiple species that have different dynamics. We formulate the discretized problem using a new type of entropy-regularized multimarginal optimal transport problems where the cost is a decomp ...

2023

On the Validity of Consensus

Rachid Guerraoui, Jovan Komatovic, Pierre Philippe Civit, Manuel José Ribeiro Vidigueira, Seth Gilbert

The Byzantine consensus problem involves.. processes, out of which t < n could be faulty and behave arbitrarily. Three properties characterize consensus: (1) termination, requiring correct (nonfaulty) processes to eventually reach a decision, (2) agreement ...

New York2023

Continuation Methods For Riemannian Optimization

Daniel Kressner, Axel Elie Joseph Séguin

Numerical continuation in the context of optimization can be used to mitigate convergence issues due to a poor initial guess. In this work, we extend this idea to Riemannian optimization problems, that is, the minimization of a target function on a Riemann ...

SIAM PUBLICATIONS2022

Blind as a bat: spatial perception without sight

Frederike Dümbgen

Among our five senses, we rely mostly on audition and vision to perceive an environment. Our ears are able to detect stimuli from all directions, especially from obstructed and far-away objects. Even in smoke, harsh weather conditions, or at night â situ ...

EPFL2021

REX technologies for profiling and decoding the electrophile signaling axes mediated by Rosetta Stone proteins

Yimon Aye, Daniel Ahmet Urul

It is now clear that some cysteines on some proteins are highly tuned to react with electrophiles. Based on numerous studies, it is also established that electrophile sensing underpins rewiring of several critical signaling processes. These electrophile-se ...

ACADEMIC PRESS LTD-ELSEVIER SCIENCE LTD2020

A mathematical model of the human heart

Alfio Quarteroni

In this paper, we present a mathematical model able to simulate the cardiac function. We first describe the basic physical principles behind the mathematical equations, then we illustrate a few examples of application to problems of clinical relevance. ...

PENSIERO SCIENTIFICO EDITOR2020

Stationary Structures near the Kolmogorov and Poiseuille Flows in the 2d Euler Equations

Klaus Martin Widmayer

We study the behavior of solutions to the incompressible 2d Euler equations near two canonical shear flows with critical points, the Kolmogorov and Poiseuille flows, with consequences for the associated Navier-Stokes problems. We exhibit a large family of ...

2020

What graph neural networks cannot learn: depth vs width

Andreas Loukas

This paper studies the expressive power of graph neural networks falling within the message-passing framework (GNNmp). Two results are presented. First, GNNmp are shown to be Turing universal under sufficient conditions on their depth, width, node attribut ...

2020

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search