Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance

13 April 2023

Papers citing "Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance"

10 / 10 papers shown

Title
Concept Activation Regions: A Generalized Framework For Concept-Based Explanations Jonathan Crabbé M. Schaar 53 46 0 22 Sep 2022
Self-Interpretable Model with TransformationEquivariant Interpretation Yipei Wang Xiaoqian Wang 26 23 0 09 Nov 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 174 1,104 0 27 Apr 2021
What Do We Want From Explainable Artificial Intelligence (XAI)? -- A Stakeholder Perspective on XAI and a Conceptual Model Guiding Interdisciplinary XAI Research Markus Langer Daniel Oster Timo Speith Holger Hermanns Lena Kästner Eva Schmidt Andreas Sesing Kevin Baum XAI 53 415 0 15 Feb 2021
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials Simon L. Batzner Albert Musaelian Lixin Sun Mario Geiger J. Mailoa M. Kornbluth N. Molinari Tess E. Smidt Boris Kozinsky 200 1,232 0 08 Jan 2021
On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location O. Kayhan J. C. V. Gemert 209 232 0 16 Mar 2020
DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in Neural Networks D. Gopinath Guy Katz C. Păsăreanu Clark W. Barrett AAML 42 87 0 02 Oct 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 242 3,681 0 28 Feb 2017
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 297 10,216 0 16 Nov 2016
SMOTE: Synthetic Minority Over-sampling Technique Nitesh V. Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 163 25,247 0 09 Jun 2011