ANN-aided incremental multiscale-remodelling-based finite strain poroelasticity

no code implementations • 11 Mar 2021 • Hamidreza Dehghani, Andreas Zilian

The full effects of the interdependency between the properties and response of macro and micro scales are considered for the first time providing more accurate predictive analysis of fluid-saturated porous media which is studied via a numerical consolidation example.

Computational Engineering, Finance, and Science

A hybrid MGA-MSGD ANN training approach for approximate solution of linear elliptic PDEs

no code implementations • 18 Dec 2020 • Hamidreza Dehghani, Andreas Zilian

Unlike classical PDE approximation methods such as finite differences or the finite element method, there is no need to establish and reconstruct the physical field quantity throughout the computational domain in order to predict the mechanical response at specific locations of interest.

Semantic and Relational Spaces in Science of Science: Deep Learning Models for Article Vectorisation

1 code implementation • 5 Nov 2020 • Diego Kozlowski, Jennifer Dusdal, Jun Pang, Andreas Zilian

Our results show that using NLP we can encode a semantic space of articles, while with GNN we are able to build a relational space where the social practices of a research community are also encoded.