Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy

24 June 2021

Christopher J. Anders

Papers citing "Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy"

47 / 47 papers shown

Title
Investigating the Relationship Between Debiasing and Artifact Removal using Saliency Maps Lukasz Sztukiewicz Ignacy Stepka Michał Wiliński Jerzy Stefanowski 133 0 0 28 Feb 2025
Optimizing Explanations by Network Canonization and Hyperparameter Search Frederik Pahde Galip Umit Yolcu Alexander Binder Wojciech Samek Sebastian Lapuschkin 99 11 0 30 Nov 2022
OpenXAI: Towards a Transparent Evaluation of Model Explanations Chirag Agarwal Dan Ley Satyapriya Krishna Eshika Saxena Martin Pawelczyk Nari Johnson Isha Puri Marinka Zitnik Himabindu Lakkaraju XAI 69 145 0 22 Jun 2022
From Attribution Maps to Human-Understandable Explanations through Concept Relevance Propagation Reduan Achtibat Maximilian Dreyer Ilona Eisenbraun S. Bosse Thomas Wiegand Wojciech Samek Sebastian Lapuschkin FAtt 68 142 0 07 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
Measurably Stronger Explanation Reliability via Model Canonization Franz Motzkus Leander Weber Sebastian Lapuschkin FAtt 40 8 0 14 Feb 2022
Navigating Neural Space: Revisiting Concept Activation Vectors to Overcome Directional Divergence Frederik Pahde Maximilian Dreyer Leander Weber Moritz Weckbecker Christopher J. Anders Thomas Wiegand Wojciech Samek Sebastian Lapuschkin 118 10 0 07 Feb 2022
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects Oliver T. Unke Stefan Chmiela M. Gastegger Kristof T. Schütt H. E. Sauceda K. Müller 191 254 0 01 May 2021
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 654 41,103 0 22 Oct 2020
A Unifying Review of Deep and Shallow Anomaly Detection Lukas Ruff Jacob R. Kauffmann Robert A. Vandermeulen G. Montavon Wojciech Samek Marius Kloft Thomas G. Dietterich Klaus-Robert Muller UQCV 117 800 0 24 Sep 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
Array Programming with NumPy Charles R. Harris K. Millman S. Walt R. Gommers Pauli Virtanen ... Tyler Reddy Warren Weckesser Hameer Abbasi C. Gohlke T. Oliphant 154 14,959 0 18 Jun 2020
Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI L. Arras Ahmed Osman Wojciech Samek XAI AAML 63 157 0 16 Mar 2020
Breaking Batch Normalization for better explainability of Deep Neural Networks through Layer-wise Relevance Propagation M. Guillemot C. Heusele R. Korichi S. Schnebert Liming Chen FAtt 33 18 0 24 Feb 2020
Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning Seul-Ki Yeom P. Seegerer Sebastian Lapuschkin Alexander Binder Simon Wiedemann K. Müller Wojciech Samek CVBM 63 207 0 18 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 511 42,449 0 03 Dec 2019
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 121 6,269 0 22 Oct 2019
Towards Best Practice in Explaining Neural Network Decisions with LRP M. Kohlbrenner Alexander Bauer Shinichi Nakajima Alexander Binder Wojciech Samek Sebastian Lapuschkin 76 149 0 22 Oct 2019
Understanding Deep Networks via Extremal Perturbations and Smooth Masks Ruth C. Fong Mandela Patrick Andrea Vedaldi AAML 71 416 0 18 Oct 2019
Explaining and Interpreting LSTMs L. Arras Jose A. Arjona-Medina Michael Widrich G. Montavon Michael Gillhofer K. Müller Sepp Hochreiter Wojciech Samek FAtt AI4TS 53 79 0 25 Sep 2019
InterpretML: A Unified Framework for Machine Learning Interpretability Harsha Nori Samuel Jenkins Paul Koch R. Caruana AI4CE 153 487 0 19 Sep 2019
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn Sebastian Lapuschkin S. Wäldchen Alexander Binder G. Montavon Wojciech Samek K. Müller 100 1,015 0 26 Feb 2019
iNNvestigate neural networks! Maximilian Alber Sebastian Lapuschkin P. Seegerer Miriam Hagele Kristof T. Schütt G. Montavon Wojciech Samek K. Müller Sven Dähne Pieter-Jan Kindermans 59 348 0 13 Aug 2018
Computationally Efficient Measures of Internal Neuron Importance Avanti Shrikumar Jocelin Su A. Kundaje FAtt 44 29 0 26 Jul 2018
RISE: Randomized Input Sampling for Explanation of Black-box Models Vitali Petsiuk Abir Das Kate Saenko FAtt 181 1,171 0 19 Jun 2018
How Important Is a Neuron? Kedar Dhamdhere Mukund Sundararajan Qiqi Yan FAtt GNN 60 130 0 30 May 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 129 3,961 0 06 Feb 2018
SmoothGrad: removing noise by adding noise D. Smilkov Nikhil Thorat Been Kim F. Viégas Martin Wattenberg FAtt ODL 204 2,226 0 12 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 21,939 0 22 May 2017
Learning how to explain neural networks: PatternNet and PatternAttribution Pieter-Jan Kindermans Kristof T. Schütt Maximilian Alber K. Müller D. Erhan Been Kim Sven Dähne XAI FAtt 76 339 0 16 May 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 201 3,873 0 10 Apr 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 188 5,989 0 04 Mar 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 303 20,023 0 07 Oct 2016
Top-down Neural Attention by Excitation Backprop Jianming Zhang Zhe Lin Jonathan Brandt Xiaohui Shen Stan Sclaroff 81 947 0 01 Aug 2016
TensorFlow: A system for large-scale machine learning Martín Abadi P. Barham Jianmin Chen Zhiwen Chen Andy Davis ... Vijay Vasudevan Pete Warden Martin Wicke Yuan Yu Xiaoqiang Zhang GNN AI4CE 433 18,361 0 27 May 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 340 7,985 0 23 May 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
Explaining NonLinear Classification Decisions with Deep Taylor Decomposition G. Montavon Sebastian Lapuschkin Alexander Binder Wojciech Samek Klaus-Robert Muller FAtt 60 737 0 08 Dec 2015
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks Sebastian Bach Alexander Binder G. Montavon K. Müller Wojciech Samek 82 199 0 01 Dec 2015
Evaluating the visualization of what a Deep Neural Network has learned Wojciech Samek Alexander Binder G. Montavon Sebastian Lapuschkin K. Müller XAI 136 1,194 0 21 Sep 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 463 43,305 0 11 Feb 2015
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 248 4,672 0 21 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.6K 100,386 0 04 Sep 2014
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 1.7K 39,547 0 01 Sep 2014
Caffe: Convolutional Architecture for Fast Feature Embedding Yangqing Jia Evan Shelhamer Jeff Donahue Sergey Karayev Jonathan Long Ross B. Girshick S. Guadarrama Trevor Darrell VLM BDL 3DV 274 14,711 0 20 Jun 2014
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 595 15,882 0 12 Nov 2013