Hubris Benchmarking with AmbiGANs: Assessing Model Overconfidence with Synthetic Ambiguous Data

Lecture notes in computer science, pp. 476–491

Authors 4

1. Cátia Teixeira corresponding

   Universidade do Porto

   Affiliation as printed

   Artificial Intelligence and Computer Science Laboratory, Faculty of Engineering, University of Porto, Porto, Portugal

2. I. L. V. GOMES Aachen Leiden Institute of Advanced Computer Science

   Leiden University · Universidade do Porto

   Affiliation as printed

   Artificial Intelligence and Computer Science Laboratory, Faculty of Engineering, University of Porto, Porto, Portugal

   Leiden Institute of Advanced Computer Science, Leiden University, Leiden, The Netherlands

3. Carlos Soares

   Universidade do Porto · Fraunhofer Portugal Research

   Affiliation as printed

   Artificial Intelligence and Computer Science Laboratory, Faculty of Engineering, University of Porto, Porto, Portugal

   Fraunhofer Portugal AICOS, Porto, Portugal

4. Jan N. van Rijn Aachen Leiden Institute of Advanced Computer Science

   Leiden University

   Affiliation as printed

   Leiden Institute of Advanced Computer Science, Leiden University, Leiden, The Netherlands