208 citations · 209 across the 2 of their papers we have counts for
5 papers
Decoupling Time and Space: A Temporally Conditioned Refinement for EEG Source Imaging
Marco Morik, Jesse Palarus, Carmen Vidaurre +2
Electroencephalography (EEG) offers millisecond temporal resolution, but inferring underlying neural sources is a severely ill-posed spatial inverse problem. While deep learning ha…
Towards Fast and Disentangled Counterfactuals for Visual Foundation Models
Sidney Bender, Benedikt Kunz, Ahmed Zeid +3
Foundation models remain vulnerable to spurious correlations and ``Clever Hans'' strategies. Explainable machine learning can find and remove such strategies for classifiers withou…
Controlling Fairness and Bias in Dynamic Learning-to-Rank
Marco Morik, Ashudeep Singh, Jessica Hong +1
Rankings are the primary interface through which many online platforms match users to items (e.g. news, products, music, video). In these two-sided markets, not only the users draw…
Listing All Maximal -Plexes in Temporal Graphs
Matthias Bentert, Anne-Sophie Himmel, Hendrik Molter +3
Many real-world networks evolve over time, that is, new contacts appear and old contacts may disappear. They can be modeled as temporal graphs where interactions between vertices (…
The Complexity of Routing with Few Collisions
Till Fluschnik, Marco Morik, Manuel Sorge
We study the computational complexity of routing multiple objects through a network in such a way that only few collisions occur: Given a graph with two distinct terminal verti…