8 citations · 15 across the 3 of their papers we have counts for
4 papers · 1 filter
B-cosification: Transforming Deep Neural Networks to be Inherently Interpretable
Shreyash Arya, Sukrut Rao, Moritz Böhle +1
B-cos Networks have been shown to be effective for obtaining highly human interpretable explanations of model decisions by architecturally enforcing stronger alignment between inpu…
Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated Concept Discovery
Sukrut Rao, Sweta Mahajan, Moritz Böhle +1
Concept Bottleneck Models (CBMs) have recently been proposed to address the 'black-box' problem of deep neural networks, by first mapping images to a human-understandable concept s…
Temperature Schedules for Self-Supervised Contrastive Methods on Long-Tail Data
Anna Kukleva, Moritz Böhle, Bernt Schiele +2
Most approaches for self-supervised learning (SSL) are optimised on curated balanced datasets, e.g. ImageNet, despite the fact that natural data usually exhibits long-tail distribu…
Holistically Explainable Vision Transformers
Moritz Böhle, Mario Fritz, Bernt Schiele
Transformers increasingly dominate the machine learning landscape across many tasks and domains, which increases the importance for understanding their outputs. While their attenti…