Semi-Empirical Data Compression for Heliophysics Space Mission Data
| dc.contributor.author | da Silva, Daniel | |
| dc.contributor.author | Bard, Christopher | |
| dc.contributor.author | Thompson, Barbara | |
| dc.contributor.author | Dorelli, John | |
| dc.contributor.author | Thomas, Brian | |
| dc.contributor.author | Barrie, Alex | |
| dc.date.accessioned | 2023-11-30T19:54:01Z | |
| dc.date.available | 2023-11-30T19:54:01Z | |
| dc.date.issued | 2022-03 | |
| dc.description | 2022 Machine Learning in Heliophysics Conference; Boulder, CO, USA; March 21-25, 2022 | |
| dc.description.sponsorship | We thank the Center for HelioAnalytics for the very important seed funding and community support, as well as the AWS Helioweb resources provided by Brian Thomas via the NASA/GSFC Heliophysics Sciences Division. | |
| dc.description.uri | https://helioanalytics.io/static/content/posters/ml-helio_2022_data_compression.pdf | |
| dc.format.extent | 1 page | |
| dc.genre | posters | |
| dc.identifier.uri | http://hdl.handle.net/11603/30985 | |
| dc.language.iso | en_US | |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Goddard Planetary Heliophysics Institute (GPHI) | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.rights | This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law. | |
| dc.rights | Public Domain Mark 1.0 | en |
| dc.rights.uri | https://creativecommons.org/publicdomain/mark/1.0/ | |
| dc.title | Semi-Empirical Data Compression for Heliophysics Space Mission Data | |
| dc.type | Image | |
| dcterms.creator | https://orcid.org/0000-0001-7537-3539 |