Revealing Similar Semantics Inside CNNs: An Interpretable Concept-based Comparison of Feature Spaces

30 April 2023

Papers citing "Revealing Similar Semantics Inside CNNs: An Interpretable Concept-based Comparison of Feature Spaces"

20 / 20 papers shown

Title
HINT: Hierarchical Neuron Concept Explainer Andong Wang Wei-Ning Lee Xiaojuan Qi 55 19 0 27 Mar 2022
Concept Embedding Analysis: A Review Gesina Schwalbe 46 28 0 25 Mar 2022
Enabling Verification of Deep Neural Networks in Perception Tasks Using Fuzzy Logic and Concept Embeddings Gesina Schwalbe Christian Wirth Ute Schmid AAML 26 7 0 03 Jan 2022
Now You See Me (CME): Concept-based Model Extraction Dmitry Kazhdan B. Dimanov M. Jamnik Pietro Lio Adrian Weller 46 75 0 25 Oct 2020
TIDE: A General Toolbox for Identifying Object Detection Errors Daniel Bolya Sean Foley James Hays Judy Hoffman 76 195 0 18 Aug 2020
Concept Bottleneck Models Pang Wei Koh Thao Nguyen Y. S. Tang Stephen Mussmann Emma Pierson Been Kim Percy Liang 94 821 0 09 Jul 2020
Invertible Concept-based Explanations for CNN Models with Non-negative Concept Activation Vectors Ruihan Zhang Prashan Madumal Tim Miller Krista A. Ehinger Benjamin I. P. Rubinstein FAtt 53 104 0 27 Jun 2020
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 116 6,254 0 22 Oct 2019
Semantics for Global and Local Interpretation of Deep Neural Networks Jindong Gu Volker Tresp AI4CE 59 14 0 21 Oct 2019
Searching for MobileNetV3 Andrew G. Howard Mark Sandler Grace Chu Liang-Chieh Chen Bo Chen ... Yukun Zhu Ruoming Pang Vijay Vasudevan Quoc V. Le Hartwig Adam 340 6,772 0 06 May 2019
Understanding Neural Networks via Feature Visualization: A survey Anh Nguyen J. Yosinski Jeff Clune FAtt 63 161 0 18 Apr 2019
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn Sebastian Lapuschkin S. Wäldchen Alexander Binder G. Montavon Wojciech Samek K. Müller 89 1,012 0 26 Feb 2019
YOLOv3: An Incremental Improvement Joseph Redmon Ali Farhadi ObjD 109 21,442 0 08 Apr 2018
Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters in Deep Neural Networks Ruth C. Fong Andrea Vedaldi FAtt 68 264 0 10 Jan 2018
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim Martin Wattenberg Justin Gilmer Carrie J. Cai James Wexler F. Viégas Rory Sayres FAtt 211 1,838 0 30 Nov 2017
Interpreting CNN Knowledge via an Explanatory Graph Quanshi Zhang Ruiming Cao Feng Shi Ying Nian Wu Song-Chun Zhu FAtt GNN SSL 56 242 0 05 Aug 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 289 19,981 0 07 Oct 2016
European Union regulations on algorithmic decision-making and a "right to explanation" B. Goodman Seth Flaxman FaML AILaw 63 1,899 0 28 Jun 2016
Model-Agnostic Interpretability of Machine Learning Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 84 838 0 16 Jun 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 250 9,308 0 14 Dec 2015