Search Results for author:
Found 2 papers, 1 papers with code
Towards Explainable Automated Neuroanatomy
It is based on the automated recognition of interpretable features obtained by analyzing the shapes of cells.
Learning Accurate and Interpretable Decision Rule Sets from Neural Networks
Each neuron in the first layer directly maps to an interpretable if-then rule after training, and the output neuron in the second layer directly maps to a disjunction of the first-layer rules to form the decision rule set.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
