77 citations · 148 across the 7 of their papers we have counts for
4 papers · 1 filter
Identifying Properties of Real-World Optimisation Problems through a Questionnaire
Koen van der Blom, Timo M. Deist, Vanessa Volz +5
Optimisation algorithms are commonly compared on benchmarks to get insight into performance differences. However, it is not clear how closely benchmarks match the properties of rea…
Multi-objective Optimization by Uncrowded Hypervolume Gradient Ascent
Timo M. Deist, Stefanus C. Maree, Tanja Alderliesten +1
Evolutionary algorithms (EAs) are the preferred method for solving black-box multi-objective optimization problems, but when gradients of the objective functions are available, it…
Towards Realistic Optimization Benchmarks: A Questionnaire on the Properties of Real-World Problems
Koen van der Blom, Timo M. Deist, Tea Tušar +5
Benchmarks are a useful tool for empirical performance comparisons. However, one of the main shortcomings of existing benchmarks is that it remains largely unclear how they relate…
An End-to-end Deep Learning Approach for Landmark Detection and Matching in Medical Images
Monika Grewal, Timo M. Deist, Jan Wiersma +2
Anatomical landmark correspondences in medical images can provide additional guidance information for the alignment of two images, which, in turn, is crucial for many medical appli…