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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 80 11 0 26 Jul 2023
Why Should I Choose You? AutoXAI: A Framework for Selecting and Tuning eXplainable AI Solutions Robin Cugny Julien Aligon Max Chevalier G. Roman-Jimenez O. Teste 48 14 0 06 Oct 2022
SAFARI: Versatile and Efficient Evaluations for Robustness of Interpretability Wei Huang Xingyu Zhao Gao Jin Xiaowei Huang AAML 59 30 0 19 Aug 2022
OmniXAI: A Library for Explainable AI Wenzhuo Yang Hung Le Tanmay Laud Silvio Savarese Guosheng Lin SyDa 37 40 0 01 Jun 2022
Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond Anna Hedström Leander Weber Dilyara Bareeva Daniel G. Krakowczyk Franz Motzkus Wojciech Samek Sebastian Lapuschkin Marina M.-C. Höhne XAI ELM 47 175 0 14 Feb 2022
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI Meike Nauta Jan Trienes Shreyasi Pathak Elisa Nguyen Michelle Peters Yasmin Schmitt Jorg Schlotterer M. V. Keulen C. Seifert ELM XAI 100 409 0 20 Jan 2022
High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach A. Blattmann Dominik Lorenz Patrick Esser Bjorn Ommer 3DV 431 15,515 0 20 Dec 2021
Interactive Analysis of CNN Robustness Stefan Sietzen Mathias Lechner Judy Borowski Ramin Hasani Manuela Waldner AAML 62 10 0 14 Oct 2021
Synthetic Benchmarks for Scientific Research in Explainable Machine Learning Yang Liu Sujay Khandagale Colin White Willie Neiswanger 105 66 0 23 Jun 2021
An Experimental Study of Semantic Continuity for Deep Learning Models Shangxi Wu Dongyuan Lu Xian Zhao Lizhang Chen Jitao Sang 68 2 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 133 843 0 16 Sep 2020
InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs Yujun Shen Ceyuan Yang Xiaoou Tang Bolei Zhou GAN CVBM 65 599 0 18 May 2020
Benchmarking Attribution Methods with Relative Feature Importance Mengjiao Yang Been Kim FAtt XAI 69 141 0 23 Jul 2019
RISE: Randomized Input Sampling for Explanation of Black-box Models Vitali Petsiuk Abir Das Kate Saenko FAtt 181 1,171 0 19 Jun 2018
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 21,939 0 22 May 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 305 20,023 0 07 Oct 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 16,990 0 16 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,020 0 10 Dec 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.8K 150,115 0 22 Dec 2014
Measuring and testing dependence by correlation of distances G. Székely Maria L. Rizzo N. K. Bakirov 274 2,599 0 28 Mar 2008