Subspace graph networks for real-time granular flow simulation with applications to machine-terrain interactions-Reference-Cited by-同舟云学术

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Subspace graph networks for real-time granular flow simulation with applications to machine-terrain interactions

Published:2024-09 Issue: Volume:135 Page:108765
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Haeri Amin^ORCID,Holz Daniel^ORCID,Skonieczny Krzysztof^ORCID

Funder

Mitacs

Natural Sciences and Engineering Research Council of Canada

Publisher

Elsevier BV

Reference85 articles.

1. TensorFlow: Large-scale machine learning on heterogeneous distributed systems;Abadi,2016

2. Graph network simulators can learn discontinuous, rigid contact dynamics;Allen,2023

3. Optimizing Cubature for efficient integration of subspace deformations;An;ACM Trans. Graph.,2008

4. The logical expressiveness of graph neural networks;Barceló,2020

5. Relational inductive biases, deep learning, and graph networks;Battaglia,2018

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