Reduced-Order Modeling for Physical Simulation: From the Classical to the Neural
Name
3736539.3737842.pdf
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821.73 KB
Format
Adobe PDF
Checksum (MD5)
6918b0438628b6425350bb2ad7451eaf
Author(s)
Levin, David IW
Chen, Peter Yichen
Grinspun, Eitan
Date Issued
August 19, 2025
Publisher
ACM|Special Interest Group on Computer Graphics and Interactive Techniques Conference
Citation
David IW Levin, Peter Yichen Chen, and Eitan Grinspun. 2025. Reduced-Order Modeling for Physical Simulation: From the Classical to the Neural. In Proceedings of the Special Interest Group on Computer Graphics and Interactive Techniques Conference Frontiers (SIGGRAPH Frontiers '25). Association for Computing Machinery, New York, NY, USA, Article 15, 1–2.
Version
Final published version
Abstract
This workshop aims to explore the evolution of subspace methods
in physical simulation, tracing their origins from classical engineering formulations to cutting-edge neural techniques. By gathering
leading researchers, students, and practitioners, the session will
serve as a platform for cross-disciplinary dialogue, education, and
community building around model reduction techniques in graphics and simulation.
Description
SIGGRAPH Frontiers ’25, Vancouver, BC, Canada
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3736539.3737842
