Scalable stellar evolution forecasting — Deep learning emulation versus hierarchical nearest-neighbor interpolation

View Publication
Abstract:
No abstract specified

SEEK ID: https://publications.h-its.org/publications/2040

Filename: aa47118-23.pdf 

Format: PDF document

Size: 18.6 MB

SEEK ID: https://publications.h-its.org/publications/2040

DOI: 10.1051/0004-6361/202347118

Research Groups: Computational Statistics

Publication type: Journal

Journal: Astronomy & Astrophysics

Publisher: EDP Sciences

Citation: Astronomy & Astrophysics, 681:A86

Date Published: 19th Jan 2024

URL:

Registered Mode: manually

Authors: K. Maltsev, F. R. N. Schneider, F. K. Röpke, A. I. Jordan, G. A. Qadir, W. E. Kerzendorf, K. Riedmiller, P. van der Smagt

Citation
Maltsev, K., Schneider, F. R. N., Röpke, F. K., Jordan, A. I., Qadir, G. A., Kerzendorf, W. E., Riedmiller, K., & van der Smagt, P. (2024). Scalable stellar evolution forecasting. In Astronomy & Astrophysics (Vol. 681, p. A86). EDP Sciences. https://doi.org/10.1051/0004-6361/202347118
Activity

Views: 136   Downloads: 1

Created: 25th Feb 2025 at 15:10

Last updated: 25th Feb 2025 at 15:11

help Tags

This item has not yet been tagged.

help Attributions

None

Powered by
 (v.1.15.2)
About HITS Publication SEEK | About HITS-Publication-SEEK | Funding and Programmes | Credits
Copyright © 2008 - 2024 The University of Manchester and HITS gGmbH