23 citations · 41 across the 6 of their papers we have counts for
7 papers
How Can Machine Learning Emulators Best Support Climate Science?
Luca Schmidt, Nina Effenberger, Vitus Benson +5
For decades, physics-based climate models have been used to provide insights for climate decision-making. Their application is, however, constrained by significant computational an…
Capturing Polysemanticity with PRISM: A Multi-Concept Feature Description Framework
Laura Kopf, Nils Feldhus, Kirill Bykov +4
Automated interpretability research aims to identify concepts encoded in neural network features to enhance human understanding of model behavior. Within the context of large langu…
Deep Learning Meets Teleconnections: Improving S2S Predictions for European Winter Weather
Philine L. Bommer, Marlene Kretschmer, Fiona R. Spuler +2
Predictions on subseasonal-to-seasonal (S2S) timescales--ranging from two weeks to two month--are crucial for early warning systems but remain challenging owing to chaos in the cli…
CoSy: Evaluating Textual Explanations of Neurons
Laura Kopf, Philine Lou Bommer, Anna Hedström +3
A crucial aspect of understanding the complex nature of Deep Neural Networks (DNNs) is the ability to explain learned concepts within their latent representations. While methods ex…
Finding the right XAI method -- A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science
Philine Bommer, Marlene Kretschmer, Anna Hedström +2
Explainable artificial intelligence (XAI) methods shed light on the predictions of machine learning algorithms. Several different approaches exist and have already been applied in…
The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus
Anna Hedström, Philine Bommer, Kristoffer K. Wickstrøm +3
One of the unsolved challenges in the field of Explainable AI (XAI) is determining how to most reliably estimate the quality of an explanation method in the absence of ground truth…
Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series
Daniel Kramer, Philine Lou Bommer, Carlo Tombolini +2
Empirically observed time series in physics, biology, or medicine, are commonly generated by some underlying dynamical system (DS) which is the target of scientific interest. There…