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Marc-Andre Schulz

2 accepted papers

2026

Brain-Semantoks: Learning Semantic Tokens of Brain Dynamics with a Self-Distilled Foundation Model

ICLR 2026poster

The development of foundation models for functional magnetic resonance imaging (fMRI) time series holds significant promise for predicting phenotypes related to disease and cognition. Current models, however, are often trained using a mask-and-reconstruct objective on small brain regions. This focus…

Cited by 0SourcecodeScholar
2021

FIMAP: Feature Importance by Minimal Adversarial Perturbation

AAAI 2021technical

Instance-based model-agnostic feature importance explanations (LIME, SHAP, L2X) are a popular form of algorithmic transparency. These methods generally return either a weighting or subset of input features as an explanation for the classification of an instance. An alternative literature argues inst…

Cited by 20SourcePDFScholar