Neural network attribution methods for problems in geoscience: A novel synthetic benchmark dataset

Despite the increasingly successful application of neural networks to many problems in the geosciences, their complex and nonlinear structure makes the interpretation of their predictions difficult, which limits model trust and does not allow scientists to gain physical insights about the problem at...

وصف كامل

التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Antonios Mamalakis, Imme Ebert-Uphoff, Elizabeth A. Barnes
التنسيق: مقال
اللغة:English
منشور في: Cambridge University Press 2022-01-01
سلاسل:Environmental Data Science
الموضوعات:
الوصول للمادة أونلاين:https://www.cambridge.org/core/product/identifier/S2634460222000073/type/journal_article

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