GeSS: Benchmarking Geometric Deep Learning under Scientific Applications with Distribution Shifts
GeSS: Benchmarking Geometric Deep Learning under Scientific Applications with Distribution Shifts
About this item
Full title
Author / Creator
Zou, Deyu , Liu, Shikun , Miao, Siqi , Fung, Victor , Chang, Shiyu and Pan, Li
Publisher
Ithaca: Cornell University Library, arXiv.org
Journal title
Language
English
Formats
Publication information
Publisher
Ithaca: Cornell University Library, arXiv.org
Subjects
More information
Scope and Contents
Contents
Geometric deep learning (GDL) has gained significant attention in scientific fields, for its proficiency in modeling data with intricate geometric structures. However, very few works have delved into its capability of tackling the distribution shift problem, a prevalent challenge in many applications. To bridge this gap, we propose GeSS, a comprehe...
Alternative Titles
Full title
GeSS: Benchmarking Geometric Deep Learning under Scientific Applications with Distribution Shifts
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2878323597
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2878323597
Other Identifiers
E-ISSN
2331-8422
