Interpretability Beyond Classification Output: Semantic Bottleneck
Networks

Interpretability Beyond Classification Output: Semantic Bottleneck Networks

25 July 2019

Mario Fritz

Bernt Schiele

Papers citing "Interpretability Beyond Classification Output: Semantic Bottleneck Networks"

19 / 19 papers shown

Title
Show and Tell: Visually Explainable Deep Neural Nets via Spatially-Aware Concept Bottleneck Models Itay Benou Tammy Riklin-Raviv 67 0 0 27 Feb 2025
COMIX: Compositional Explanations using Prototypes S. Sivaprasad D. Kangin Plamen Angelov Mario Fritz 136 0 0 10 Jan 2025
Image-guided topic modeling for interpretable privacy classification Alina Elena Baia Andrea Cavallaro 37 0 0 27 Sep 2024
Multi-Scale Grouped Prototypes for Interpretable Semantic Segmentation Hugo Porta Emanuele Dalsasso Diego Marcos D. Tuia 93 0 0 14 Sep 2024
DEPICT: Diffusion-Enabled Permutation Importance for Image Classification Tasks Sarah Jabbour Gregory Kondas Ella Kazerooni Michael Sjoding David Fouhey Jenna Wiens FAtt DiffM 47 1 0 19 Jul 2024
Understanding Multimodal Deep Neural Networks: A Concept Selection View Chenming Shang Hengyuan Zhang Hao Wen Yujiu Yang 43 5 0 13 Apr 2024
Sparse Concept Bottleneck Models: Gumbel Tricks in Contrastive Learning Andrei Semenov Vladimir Ivanov Aleksandr Beznosikov Alexander Gasnikov 29 6 0 04 Apr 2024
Interpreting Pretrained Language Models via Concept Bottlenecks Zhen Tan Lu Cheng Song Wang Yuan Bo Jundong Li Huan Liu LRM 29 20 0 08 Nov 2023
Hierarchical Explanations for Video Action Recognition Sadaf Gulshad Teng Long N. V. Noord FAtt 18 6 0 01 Jan 2023
Concept Embedding Analysis: A Review Gesina Schwalbe 19 28 0 25 Mar 2022
Editing a classifier by rewriting its prediction rules Shibani Santurkar Dimitris Tsipras Mahalaxmi Elango David Bau Antonio Torralba A. Madry KELM 175 89 0 02 Dec 2021
Image Classification with Consistent Supporting Evidence Peiqi Wang Ruizhi Liao Daniel Moyer Seth Berkowitz Steven Horng Polina Golland 34 2 0 13 Nov 2021
Toward a Unified Framework for Debugging Concept-based Models A. Bontempelli Fausto Giunchiglia Andrea Passerini Stefano Teso 18 4 0 23 Sep 2021
Promises and Pitfalls of Black-Box Concept Learning Models Anita Mahinpei Justin Clark Isaac Lage Finale Doshi-Velez Weiwei Pan 31 91 0 24 Jun 2021
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts Gesina Schwalbe Bettina Finzel XAI 21 184 0 15 May 2021
Towards a Collective Agenda on AI for Earth Science Data Analysis D. Tuia R. Roscher Jan Dirk Wegner Nathan Jacobs Xiaoxiang Zhu Gustau Camps-Valls AI4CE 39 68 0 11 Apr 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 53 651 0 20 Mar 2021
Debiasing Concept-based Explanations with Causal Analysis M. T. Bahadori David Heckerman FAtt CML 6 38 0 22 Jul 2020
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 281 5,833 0 08 Jul 2016