In the past decade, the application of Neural Networks (NNs) has received increasing interest due to the growth in computing power. In the field of computational mechanics, this has led to numerous publications presenting surrogate models to assist or replace conventional simulation methods. A subset of these networks, referred to as Graph Neural Networks (GNNs) impose the graph-like structure of many physical problems as a relational inductive bias. Several time-stepper implementations of these GNNs are reported to be able to simulate the dynamic behaviour of various physical objects. Within this work, it is investigated whether such GNN-based surrogate models can be applied to simulate the dynamic behaviour of lattice structures.Upon infe...
International audienceCurrent simulation of metal forging processes use advanced finite element meth...
Metamaterials are a group of materials with artificial engineered structures that exhibits customize...
Graphs are ubiquitous in nature and can therefore serve as models for many practical but also theore...
From designing architected materials to connecting mechanical behavior across scales, computational ...
This paper investigates the structure-property relations of thin-walled lattices under dynamic longi...
Graph Neural Networks (GNNs) have exploded onto the machine learning scene in recent years owing to ...
The use of continuum models for the analysis of discrete built-up complex aerospace structures is an...
The feasibility of simulating and synthesizing substructures by computational neural network models ...
Abstract Developing accurate yet fast computational tools to simulate complex physical phenomena is ...
Machine learning (ML) and deep learning (DL) techniques have gained significant attention as reduced...
The theme of this dissertation is machine learning on graph data. Graphs are generic models of signa...
© 36th International Conference on Machine Learning, ICML 2019. All rights reserved. We explore the ...
In a particular case of behavioural model reduction by ANNs, a validity domain shortening has been f...
The human brain’s reasoning is postulated to be done by the creation of graphs from the experiences ...
Motivated by the successes in the field of deep learning, the scientific community has been increasi...
International audienceCurrent simulation of metal forging processes use advanced finite element meth...
Metamaterials are a group of materials with artificial engineered structures that exhibits customize...
Graphs are ubiquitous in nature and can therefore serve as models for many practical but also theore...
From designing architected materials to connecting mechanical behavior across scales, computational ...
This paper investigates the structure-property relations of thin-walled lattices under dynamic longi...
Graph Neural Networks (GNNs) have exploded onto the machine learning scene in recent years owing to ...
The use of continuum models for the analysis of discrete built-up complex aerospace structures is an...
The feasibility of simulating and synthesizing substructures by computational neural network models ...
Abstract Developing accurate yet fast computational tools to simulate complex physical phenomena is ...
Machine learning (ML) and deep learning (DL) techniques have gained significant attention as reduced...
The theme of this dissertation is machine learning on graph data. Graphs are generic models of signa...
© 36th International Conference on Machine Learning, ICML 2019. All rights reserved. We explore the ...
In a particular case of behavioural model reduction by ANNs, a validity domain shortening has been f...
The human brain’s reasoning is postulated to be done by the creation of graphs from the experiences ...
Motivated by the successes in the field of deep learning, the scientific community has been increasi...
International audienceCurrent simulation of metal forging processes use advanced finite element meth...
Metamaterials are a group of materials with artificial engineered structures that exhibits customize...
Graphs are ubiquitous in nature and can therefore serve as models for many practical but also theore...