2 papers
cs.LG2026
DIVERSE: Disagreement-Inducing Vector Evolution for Rashomon Set Exploration
Gilles Eerlings, Brent Zoomers, Jori Liesenborgs +2
We propose DIVERSE, a framework for systematically exploring the Rashomon set of deep neural networks, the collection of models that match a reference model's accuracy while differ…
cs.HC2024
AI-Spectra: A Visual Dashboard for Model Multiplicity to Enhance Informed and Transparent Decision-Making
Gilles Eerlings, Sebe Vanbrabant, Jori Liesenborgs +3
We present an approach, AI-Spectra, to leverage model multiplicity for interactive systems. Model multiplicity means using slightly different AI models yielding equally valid outco…