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Beyond the Veil of Similarity: Quantifying Semantic Continuity in Explainable AI

17 July 2024

Papers citing "Beyond the Veil of Similarity: Quantifying Semantic Continuity in Explainable AI"

20 / 20 papers shown

Title
The Co-12 Recipe for Evaluating Interpretable Part-Prototype Image Classifiers Meike Nauta Christin Seifert 228 16 0 26 Jul 2023
Why Should I Choose You? AutoXAI: A Framework for Selecting and Tuning eXplainable AI SolutionsInternational Conference on Information and Knowledge Management (CIKM), 2022 Robin Cugny Julien Aligon Max Chevalier G. Roman-Jimenez O. Teste 185 21 0 06 Oct 2022
SAFARI: Versatile and Efficient Evaluations for Robustness of InterpretabilityIEEE International Conference on Computer Vision (ICCV), 2022 Wei Huang Xingyu Zhao Gao Jin Xiaowei Huang AAML 249 36 0 19 Aug 2022
OmniXAI: A Library for Explainable AI Wenzhuo Yang Hung Le Tanmay Laud Silvio Savarese Guosheng Lin SyDa 226 50 0 01 Jun 2022
Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and BeyondJournal of machine learning research (JMLR), 2022 Anna Hedström Leander Weber Dilyara Bareeva Daniel G. Krakowczyk Franz Motzkus Wojciech Samek Sebastian Lapuschkin Marina M.-C. Höhne XAI ELM 293 216 0 14 Feb 2022
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AIACM Computing Surveys (ACM CSUR), 2022 Meike Nauta Jan Trienes Shreyasi Pathak Elisa Nguyen Michelle Peters Yasmin Schmitt Jorg Schlotterer M. V. Keulen C. Seifert ELM XAI 495 541 0 20 Jan 2022
High-Resolution Image Synthesis with Latent Diffusion ModelsComputer Vision and Pattern Recognition (CVPR), 2021 Robin Rombach A. Blattmann Dominik Lorenz Patrick Esser Bjorn Ommer DiffM 1.3K 20,412 0 20 Dec 2021
Interactive Analysis of CNN Robustness Stefan Sietzen Mathias Lechner Judy Borowski Ramin Hasani Manuela Waldner AAML 111 14 0 14 Oct 2021
Synthetic Benchmarks for Scientific Research in Explainable Machine Learning Yang Liu Sujay Khandagale Colin White Willie Neiswanger 202 77 0 23 Jun 2021
An Experimental Study of Semantic Continuity for Deep Learning Models Shangxi Wu Dongyuan Lu Xian Zhao Lizhang Chen Jitao Sang 207 3 0 19 Nov 2020
Captum: A unified and generic model interpretability library for PyTorch Narine Kokhlikyan Vivek Miglani Miguel Martin Edward Wang B. Alsallakh ... Alexander Melnikov Natalia Kliushkina Carlos Araya Siqi Yan Orion Reblitz-Richardson FAtt 343 1,002 0 16 Sep 2020
InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs Yujun Shen Ceyuan Yang Xiaoou Tang Bolei Zhou GAN CVBM 384 663 0 18 May 2020
Benchmarking Attribution Methods with Relative Feature Importance Mengjiao Yang Been Kim FAtt XAI 157 151 0 23 Jul 2019
RISE: Randomized Input Sampling for Explanation of Black-box Models Vitali Petsiuk Abir Das Kate Saenko FAtt 447 1,339 0 19 Jun 2018
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 2.7K 28,319 0 22 May 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based LocalizationInternational Journal of Computer Vision (IJCV), 2016 Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 840 23,616 0 07 Oct 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.9K 19,237 0 16 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 3.5K 214,399 0 10 Dec 2015
Adam: A Method for Stochastic OptimizationInternational Conference on Learning Representations (ICLR), 2014 Diederik P. Kingma Jimmy Ba ODL 4.4K 160,262 0 22 Dec 2014
Measuring and testing dependence by correlation of distances G. Székely Maria L. Rizzo N. K. Bakirov 505 2,746 0 28 Mar 2008