Marc Langheinrich

CRF-based aggregation in federated learning significantly boosts model performance by accurately reflecting client reliability and interactions, especially under data heterogeneity.

KANs become far more robust and interpretable with in-context symbolic regression, achieving near-perfect error reduction in hyperparameter sweeps.