Carefully Choose the Baseline: Lessons Learned from Applying XAI Attribution Methods for Regression Tasks in GeoscienceSource: Artificial Intelligence for the Earth Systems:;2023:;volume( 002 ):;issue: 001DOI: 10.1175/AIES-D-22-0058.1Publisher: American Meteorological Society
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| contributor author | Mamalakis, Antonios | |
| contributor author | Barnes, Elizabeth A. | |
| contributor author | Ebert-Uphoff, Imme | |
| date accessioned | 2023-08-15T10:40:19Z | |
| date available | 2023-08-15T10:40:19Z | |
| date copyright | 01 Jan. 2023 | |
| date issued | 2023 | |
| identifier other | AIES-D-22-0058.1.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4290760 | |
| language | English | |
| publisher | American Meteorological Society | |
| title | Carefully Choose the Baseline: Lessons Learned from Applying XAI Attribution Methods for Regression Tasks in Geoscience | |
| type | Journal Paper | |
| journal volume | 2 | |
| journal issue | 1 | |
| journal title | Artificial Intelligence for the Earth Systems | |
| identifier doi | 10.1175/AIES-D-22-0058.1 | |
| page | e220058 | |
| tree | Artificial Intelligence for the Earth Systems:;2023:;volume( 002 ):;issue: 001 | |
| contenttype | Fulltext |