Learn to explain yourself, when you can: Equipping Concept Bottleneck Models with the ability to abstain on their concept predictions

21 November 2022

Papers citing "Learn to explain yourself, when you can: Equipping Concept Bottleneck Models with the ability to abstain on their concept predictions"

4 / 4 papers shown

Title
Conceptual Learning via Embedding Approximations for Reinforcing Interpretability and Transparency Maor Dikter Tsachi Blau Chaim Baskin 41 0 0 13 Jun 2024
Learning to Intervene on Concept Bottlenecks David Steinmann Wolfgang Stammer Felix Friedrich Kristian Kersting 17 19 0 25 Aug 2023
Human Uncertainty in Concept-Based AI Systems Katherine M. Collins Matthew Barker M. Zarlenga Naveen Raman Umang Bhatt M. Jamnik Ilia Sucholutsky Adrian Weller Krishnamurthy Dvijotham 58 39 0 22 Mar 2023
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015