314 citations · 350 across the 8 of their papers we have counts for
Showing 2021Show all
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stat.ML2021★ 5 cited
Optimising for Interpretability: Convolutional Dynamic Alignment Networks
Moritz Böhle, Mario Fritz, Bernt Schiele
We introduce a new family of neural network models called Convolutional Dynamic Alignment Networks (CoDA Nets), which are performant classifiers with a high degree of inherent inte…
cs.LG2021
Convolutional Dynamic Alignment Networks for Interpretable Classifications
Moritz Böhle, Mario Fritz, Bernt Schiele
We introduce a new family of neural network models called Convolutional Dynamic Alignment Networks (CoDA-Nets), which are performant classifiers with a high degree of inherent inte…