13 citations · 13 across the 4 of their papers we have counts for
4 papers
Covered Information Disentanglement: Model Transparency via Unbiased Permutation Importance
João Pereira, Erik S. G. Stroes, Aeilko H. Zwinderman +1
Model transparency is a prerequisite in many domains and an increasingly popular area in machine learning research. In the medical domain, for instance, unveiling the mechanisms be…
Interpretable Models via Pairwise permutations algorithm
Troy Maaslandand, João Pereira, Diogo Bastos +4
One of the most common pitfalls often found in high dimensional biological data sets are correlations between the features. This may lead to statistical and machine learning method…
Graph Space Embedding
João Pereira, Albert Groen, Erik Stroes +1
We propose the Graph Space Embedding (GSE), a technique that maps the input into a space where interactions are implicitly encoded, with little computations required. We provide th…
Classification of Quantitative Light-Induced Fluorescence Images Using Convolutional Neural Network
Sultan Imangaliyev, Monique H. van der Veen, Catherine M. C. Volgenant +4
Images are an important data source for diagnosis and treatment of oral diseases. The manual classification of images may lead to misdiagnosis or mistreatment due to subjective err…