Black Box Explanation by Learning Image Exemplars in the Latent Feature Space

27 January 2020

Papers citing "Black Box Explanation by Learning Image Exemplars in the Latent Feature Space"

33 / 33 papers shown

Anomaly Detection in Event-triggered Traffic Time Series via Similarity LearningIEEE Transactions on Dependable and Secure Computing (IEEE TDSC), 2025

299

20 Jun 2025

Explanations Go Linear: Post-hoc Explainability for Tabular Data with Interpretable Meta-Encoding

1.2K

29 Apr 2025

Explainable AI in Time-Sensitive Scenarios: Prefetched Offline Explanation ModelIFIP Working Conference on Database Semantics (IWDS), 2025

332

06 Mar 2025

Transparent Neighborhood Approximation for Text Classifier ExplanationInternational Conference on Data Science and Advanced Analytics (DSAA), 2024

444

25 Nov 2024

Towards Explainable Artificial Intelligence (XAI): A Data Mining Perspective

Haoyi Xiong

428

09 Jan 2024

Explaining text classifiers through progressive neighborhood approximation with realistic samples

240

11 Feb 2023

Exemplars and Counterexemplars Explanations for Image Classifiers, Targeting Skin Lesion LabelingInternational Symposium on Computers and Communications (ISCC), 2021

244

18 Jan 2023

Causality-Aware Local Interpretable Model-Agnostic Explanations

Martina Cinquini

Riccardo Guidotti

CML

334

10 Dec 2022

Hub-VAE: Unsupervised Hub-based Regularization of Variational Autoencoders

Priya Mani

C. Domeniconi

BDL SSL DRL

297

18 Nov 2022

Decomposing Counterfactual Explanations for Consequential Decision Making

Martin Pawelczyk

Lea Tiyavorabun

Gjergji Kasneci

CML

197

03 Nov 2022

Explaining Classifiers by Constructing Familiar ConceptsMachine-mediated learning (ML), 2022

Johannes Schneider

M. Vlachos

223

07 Mar 2022

Benchmarking Instance-Centric Counterfactual Algorithms for XAI: From White Box to Black BoxACM Computing Surveys (ACM CSUR), 2022

480

04 Mar 2022

Analogies and Feature Attributions for Model Agnostic Explanation of Similarity Learners

Karthikeyan N. Ramamurthy

282

02 Feb 2022

Explainable Deep Image Classifiers for Skin Lesion Diagnosis

191

22 Nov 2021

XPROAX-Local explanations for text classification with progressive neighborhood approximation

Yi Cai

Arthur Zimek

Eirini Ntoutsi

221

30 Sep 2021

Interpretable Summaries of Black Box Incident Triaging with Subgroup DiscoveryInternational Conference on Data Science and Advanced Analytics (DSAA), 2021

Mehdi Kaytoue-Uberall

149

06 Aug 2021

NoiseGrad: Enhancing Explanations by Introducing Stochasticity to Model WeightsAAAI Conference on Artificial Intelligence (AAAI), 2021

362

18 Jun 2021

Understanding Prediction Discrepancies in Machine Learning Classifiers

259

12 Apr 2021

Interpretable Deep Learning: Interpretation, Interpretability, Trustworthiness, and BeyondKnowledge and Information Systems (KAIS), 2021

Haoyi Xiong

Jiang Bian

371

476

19 Mar 2021

Beyond Trivial Counterfactual Explanations with Diverse Valuable ExplanationsIEEE International Conference on Computer Vision (ICCV), 2021

David Vazquez

327

18 Mar 2021

Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and ApplicationsInformation Fusion (Inf. Fusion), 2021

457

231

07 Mar 2021

Benchmarking and Survey of Explanation Methods for Black Box ModelsData mining and knowledge discovery (DMKD), 2021

541

316

25 Feb 2021

Neural Prototype Trees for Interpretable Fine-grained Image RecognitionComputer Vision and Pattern Recognition (CVPR), 2020

Meike Nauta

Ron van Bree

C. Seifert

609

352

03 Dec 2020

ProtoPShare: Prototype Sharing for Interpretable Image Classification and Similarity DiscoveryKnowledge Discovery and Data Mining (KDD), 2020

324

143

29 Nov 2020

Explaining Differences in Classes of Discrete Sequences

Samaneh Saadat

G. Sukthankar

190

06 Nov 2020

MAIRE -- A Model-Agnostic Interpretable Rule Extraction Procedure for Explaining Classifiers

223

03 Nov 2020

A survey of algorithmic recourse: definitions, formulations, solutions, and prospects

Gilles Barthe

424

187

08 Oct 2020

Counterfactual Explanation Based on Gradual Construction for Deep Networks

297

05 Aug 2020

On quantitative aspects of model interpretability

An-phi Nguyen

María Rodríguez Martínez

291

135

15 Jul 2020

Explaining Predictions by Approximating the Local Decision Boundary

Vlado Menkovski

200

14 Jun 2020

A Generic and Model-Agnostic Exemplar Synthetization Framework for Explainable AI

235

06 Jun 2020

Cracking the Black Box: Distilling Deep Sports AnalyticsKnowledge Discovery and Data Mining (KDD), 2020

238

04 Jun 2020

A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov-Smirnov boundsNeural Networks (NN), 2020

M. Kovalev

Lev V. Utkin

AAML

367

05 May 2020