The (Un)reliability of saliency methods

2 November 2017

Pieter-Jan Kindermans

Papers citing "The (Un)reliability of saliency methods"

50 / 119 papers shown

Title
A model-agnostic approach for generating Saliency Maps to explain inferred decisions of Deep Learning Models S. Karatsiolis A. Kamilaris FAtt 29 1 0 19 Sep 2022
Explainable AI for clinical and remote health applications: a survey on tabular and time series data Flavio Di Martino Franca Delmastro AI4TS 26 91 0 14 Sep 2022
Concept-Based Techniques for "Musicologist-friendly" Explanations in a Deep Music Classifier Francesco Foscarin Katharina Hoedt Verena Praher A. Flexer Gerhard Widmer 21 11 0 26 Aug 2022
HetVis: A Visual Analysis Approach for Identifying Data Heterogeneity in Horizontal Federated Learning Xumeng Wang Wei-Neng Chen Jiazhi Xia Zhen Wen Rongchen Zhu Tobias Schreck FedML 26 20 0 16 Aug 2022
Explainable AI Algorithms for Vibration Data-based Fault Detection: Use Case-adadpted Methods and Critical Evaluation Oliver Mey Deniz Neufeld 17 21 0 21 Jul 2022
Towards ML Methods for Biodiversity: A Novel Wild Bee Dataset and Evaluations of XAI Methods for ML-Assisted Rare Species Annotations Teodor Chiaburu F. Biessmann Frank Haußer 30 2 0 15 Jun 2022
Multi-Objective Hyperparameter Optimization in Machine Learning -- An Overview Florian Karl Tobias Pielok Julia Moosbauer Florian Pfisterer Stefan Coors ... Jakob Richter Michel Lang Eduardo C. Garrido-Merchán Juergen Branke B. Bischl AI4CE 26 56 0 15 Jun 2022
Attribution-based Explanations that Provide Recourse Cannot be Robust H. Fokkema R. D. Heide T. Erven FAtt 44 18 0 31 May 2022
Backdooring Explainable Machine Learning Maximilian Noppel Lukas Peter Christian Wressnegger AAML 14 5 0 20 Apr 2022
Maximum Entropy Baseline for Integrated Gradients Hanxiao Tan FAtt 16 4 0 12 Apr 2022
XAI in the context of Predictive Process Monitoring: Too much to Reveal Ghada Elkhawaga Mervat Abuelkheir M. Reichert 12 1 0 16 Feb 2022
Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis Thomas Fel Mélanie Ducoffe David Vigouroux Rémi Cadène Mikael Capelle C. Nicodeme Thomas Serre AAML 23 41 0 15 Feb 2022
Multi-Modal Knowledge Graph Construction and Application: A Survey Xiangru Zhu Zhixu Li Xiaodan Wang Xueyao Jiang Penglei Sun Xuwu Wang Yanghua Xiao N. Yuan 28 154 0 11 Feb 2022
Investigating the fidelity of explainable artificial intelligence methods for applications of convolutional neural networks in geoscience Antonios Mamalakis E. Barnes I. Ebert‐Uphoff 19 73 0 07 Feb 2022
Visualizing Automatic Speech Recognition -- Means for a Better Understanding? Karla Markert Romain Parracone Mykhailo Kulakov Philip Sperl Ching-yu Kao Konstantin Böttinger 11 8 0 01 Feb 2022
PCACE: A Statistical Approach to Ranking Neurons for CNN Interpretability Sílvia Casacuberta Esra Suel Seth Flaxman FAtt 16 1 0 31 Dec 2021
Generating Fluent Fact Checking Explanations with Unsupervised Post-Editing Shailza Jolly Pepa Atanasova Isabelle Augenstein 28 13 0 13 Dec 2021
Improving Deep Learning Interpretability by Saliency Guided Training Aya Abdelsalam Ismail H. C. Bravo S. Feizi FAtt 18 79 0 29 Nov 2021
Evaluation of Interpretability for Deep Learning algorithms in EEG Emotion Recognition: A case study in Autism J. M. M. Torres Sara E. Medina-DeVilliers T. Clarkson M. Lerner Giuseppe Riccardi 22 34 0 25 Nov 2021
Self-Interpretable Model with TransformationEquivariant Interpretation Yipei Wang Xiaoqian Wang 29 23 0 09 Nov 2021
Defense Against Explanation Manipulation Ruixiang Tang Ninghao Liu Fan Yang Na Zou Xia Hu AAML 39 11 0 08 Nov 2021
A Survey on the Robustness of Feature Importance and Counterfactual Explanations Saumitra Mishra Sanghamitra Dutta Jason Long Daniele Magazzeni AAML 9 58 0 30 Oct 2021
Evaluating the Faithfulness of Importance Measures in NLP by Recursively Masking Allegedly Important Tokens and Retraining Andreas Madsen Nicholas Meade Vaibhav Adlakha Siva Reddy 96 35 0 15 Oct 2021
Self-explaining Neural Network with Concept-based Explanations for ICU Mortality Prediction Sayantan Kumar Sean C. Yu Thomas Kannampallil Zachary B. Abrams Andrew Michelson Philip R. O. Payne FAtt 9 7 0 09 Oct 2021
Consistent Explanations by Contrastive Learning Vipin Pillai Soroush Abbasi Koohpayegani Ashley Ouligian Dennis Fong Hamed Pirsiavash FAtt 18 21 0 01 Oct 2021
GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks Lucie Charlotte Magister Dmitry Kazhdan Vikash Singh Pietro Lió 27 48 0 25 Jul 2021
CAMERAS: Enhanced Resolution And Sanity preserving Class Activation Mapping for image saliency M. Jalwana Naveed Akhtar Bennamoun Ajmal Saeed Mian 22 54 0 20 Jun 2021
Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks Thorben Funke Megha Khosla Mandeep Rathee Avishek Anand FAtt 21 38 0 18 May 2021
Towards Rigorous Interpretations: a Formalisation of Feature Attribution Darius Afchar Romain Hennequin Vincent Guigue FAtt 31 20 0 26 Apr 2021
EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case Natalia Díaz Rodríguez Alberto Lamas Jules Sanchez Gianni Franchi Ivan Donadello S. Tabik David Filliat P. Cruz Rosana Montes Francisco Herrera 47 77 0 24 Apr 2021
Neural Network Attribution Methods for Problems in Geoscience: A Novel Synthetic Benchmark Dataset Antonios Mamalakis I. Ebert‐Uphoff E. Barnes OOD 23 75 0 18 Mar 2021
Do Input Gradients Highlight Discriminative Features? Harshay Shah Prateek Jain Praneeth Netrapalli AAML FAtt 21 57 0 25 Feb 2021
Connecting Interpretability and Robustness in Decision Trees through Separation Michal Moshkovitz Yao-Yuan Yang Kamalika Chaudhuri 25 22 0 14 Feb 2021
Neural Prototype Trees for Interpretable Fine-grained Image Recognition Meike Nauta Ron van Bree C. Seifert 68 261 0 03 Dec 2020
Reflective-Net: Learning from Explanations Johannes Schneider Michalis Vlachos FAtt OffRL LRM 54 18 0 27 Nov 2020
Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization Judy Borowski Roland S. Zimmermann Judith Schepers Robert Geirhos Thomas S. A. Wallis Matthias Bethge Wieland Brendel FAtt 36 7 0 23 Oct 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 29 48 0 19 Oct 2020
What Do You See? Evaluation of Explainable Artificial Intelligence (XAI) Interpretability through Neural Backdoors Yi-Shan Lin Wen-Chuan Lee Z. Berkay Celik XAI 24 93 0 22 Sep 2020
A simple defense against adversarial attacks on heatmap explanations Laura Rieger Lars Kai Hansen FAtt AAML 25 37 0 13 Jul 2020
Evolved Explainable Classifications for Lymph Node Metastases Iam Palatnik de Sousa M. Vellasco E. C. Silva 14 6 0 14 May 2020
Evaluating and Aggregating Feature-based Model Explanations Umang Bhatt Adrian Weller J. M. F. Moura XAI 28 218 0 01 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 29 371 0 30 Apr 2020
A Survey of Deep Learning for Scientific Discovery M. Raghu Erica Schmidt OOD AI4CE 35 120 0 26 Mar 2020
Measuring and improving the quality of visual explanations Agnieszka Grabska-Barwiñska XAI FAtt 8 3 0 14 Mar 2020
Explaining Explanations: Axiomatic Feature Interactions for Deep Networks Joseph D. Janizek Pascal Sturmfels Su-In Lee FAtt 24 143 0 10 Feb 2020
SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentation Jesse Sun Fatemeh Darbeha M. Zaidi Bo Wang AAML 9 110 0 21 Jan 2020
CXPlain: Causal Explanations for Model Interpretation under Uncertainty Patrick Schwab W. Karlen FAtt CML 29 205 0 27 Oct 2019
Seeing What a GAN Cannot Generate David Bau Jun-Yan Zhu Jonas Wulff William S. Peebles Hendrik Strobelt Bolei Zhou Antonio Torralba GAN 24 307 0 24 Oct 2019
Deep Weakly-Supervised Learning Methods for Classification and Localization in Histology Images: A Survey Jérôme Rony Soufiane Belharbi Jose Dolz Ismail Ben Ayed Luke McCaffrey Eric Granger 25 70 0 08 Sep 2019
Saccader: Improving Accuracy of Hard Attention Models for Vision Gamaleldin F. Elsayed Simon Kornblith Quoc V. Le VLM 25 70 0 20 Aug 2019