Reliable Post hoc Explanations: Modeling Uncertainty in Explainability

11 August 2020

Himabindu Lakkaraju

Papers citing "Reliable Post hoc Explanations: Modeling Uncertainty in Explainability"

25 / 25 papers shown

Title
Display Content, Display Methods and Evaluation Methods of the HCI in Explainable Recommender Systems: A Survey Weiqing Li Yue Xu Yuefeng Li Yinghui Huang 23 0 0 14 May 2025
DiCE-Extended: A Robust Approach to Counterfactual Explanations in Machine Learning Volkan Bakir Polat Goktas Sureyya Akyuz 52 0 0 26 Apr 2025
Feature Importance Depends on Properties of the Data: Towards Choosing the Correct Explanations for Your Data and Decision Trees based Models Célia Wafa Ayad Thomas Bonnier Benjamin Bosch Sonali Parbhoo Jesse Read FAtt XAI 103 0 0 11 Feb 2025
Counterfactuals As a Means for Evaluating Faithfulness of Attribution Methods in Autoregressive Language Models Sepehr Kamahi Yadollah Yaghoobzadeh 51 0 0 21 Aug 2024
Efficient and Accurate Explanation Estimation with Distribution Compression Hubert Baniecki Giuseppe Casalicchio Bernd Bischl Przemyslaw Biecek FAtt 46 3 0 26 Jun 2024
Evaluating Saliency Explanations in NLP by Crowdsourcing Xiaotian Lu Jiyi Li Zhen Wan Xiaofeng Lin Koh Takeuchi Hisashi Kashima XAI FAtt LRM 27 1 0 17 May 2024
Post-hoc and manifold explanations analysis of facial expression data based on deep learning Yang Xiao 29 0 0 29 Apr 2024
Segmentation, Classification and Interpretation of Breast Cancer Medical Images using Human-in-the-Loop Machine Learning David Vázquez-Lema E. Mosqueira-Rey Elena Hernández-Pereira Carlos Fernández-Lozano Fernando Seara-Romera Jorge Pombo-Otero LM&MA 34 1 0 29 Mar 2024
Uncertainty Quantification for Gradient-based Explanations in Neural Networks Mihir Mulye Matias Valdenegro-Toro UQCV FAtt 33 0 0 25 Mar 2024
QUCE: The Minimisation and Quantification of Path-Based Uncertainty for Generative Counterfactual Explanations J. Duell M. Seisenberger Hsuan-Wei Fu Xiuyi Fan UQCV BDL 37 1 0 27 Feb 2024
Explaining Probabilistic Models with Distributional Values Luca Franceschi Michele Donini Cédric Archambeau Matthias Seeger FAtt 37 2 0 15 Feb 2024
The Duet of Representations and How Explanations Exacerbate It Charles Wan Rodrigo Belo Leid Zejnilovic Susana Lavado CML FAtt 16 1 0 13 Feb 2024
Generating Explanations to Understand and Repair Embedding-based Entity Alignment Xiaobin Tian Zequn Sun Wei Hu 26 6 0 08 Dec 2023
Generative Perturbation Analysis for Probabilistic Black-Box Anomaly Attribution T. Idé Naoki Abe 38 4 0 09 Aug 2023
Confident Feature Ranking Bitya Neuhof Y. Benjamini FAtt 26 3 0 28 Jul 2023
Communicating Uncertainty in Machine Learning Explanations: A Visualization Analytics Approach for Predictive Process Monitoring Nijat Mehdiyev Maxim Majlatow Peter Fettke 27 2 0 12 Apr 2023
Ignore, Trust, or Negotiate: Understanding Clinician Acceptance of AI-Based Treatment Recommendations in Health Care Venkatesh Sivaraman L. Bukowski J. Levin J. Kahn Adam Perer 29 81 0 31 Jan 2023
REVEL Framework to measure Local Linear Explanations for black-box models: Deep Learning Image Classification case of study Iván Sevillano-García Julián Luengo-Martín Francisco Herrera XAI FAtt 21 7 0 11 Nov 2022
Neural Basis Models for Interpretability Filip Radenovic Abhimanyu Dubey D. Mahajan FAtt 24 46 0 27 May 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
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective Satyapriya Krishna Tessa Han Alex Gu Steven Wu S. Jabbari Himabindu Lakkaraju 177 186 0 03 Feb 2022
Metrics for saliency map evaluation of deep learning explanation methods T. Gomez Thomas Fréour Harold Mouchère XAI FAtt 69 41 0 31 Jan 2022
Post-Hoc Explanations Fail to Achieve their Purpose in Adversarial Contexts Sebastian Bordt Michèle Finck Eric Raidl U. V. Luxburg AILaw 36 77 0 25 Jan 2022
What will it take to generate fairness-preserving explanations? Jessica Dai Sohini Upadhyay Stephen H. Bach Himabindu Lakkaraju FAtt FaML 13 14 0 24 Jun 2021
Rational Shapley Values David S. Watson 23 20 0 18 Jun 2021