4 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…