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Toward Explainable AI for Regression Models
Simon Letzgus, Patrick Wagner, Jonas Lederer +3
In addition to the impressive predictive power of machine learning (ML) models, more recently, explanation methods have emerged that enable an interpretation of complex non-linear…
Deep learning for surrogate modelling of 2D mantle convection
Siddhant Agarwal, Nicola Tosi, Pan Kessel +2
Traditionally, 1D models based on scaling laws have been used to parameterized convective heat transfer rocks in the interior of terrestrial planets like Earth, Mars, Mercury and V…
Learning Domain Invariant Representations by Joint Wasserstein Distance Minimization
Léo Andeol, Yusei Kawakami, Yuichiro Wada +3
Domain shifts in the training data are common in practical applications of machine learning; they occur for instance when the data is coming from different sources. Ideally, a ML m…