ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2111.00358
  4. Cited By
A Survey on the Robustness of Feature Importance and Counterfactual
  Explanations

A Survey on the Robustness of Feature Importance and Counterfactual Explanations

30 October 2021
Saumitra Mishra
Sanghamitra Dutta
Jason Long
Daniele Magazzeni
    AAML
ArXivPDFHTML

Papers citing "A Survey on the Robustness of Feature Importance and Counterfactual Explanations"

15 / 15 papers shown
Title
Reconciling Privacy and Explainability in High-Stakes: A Systematic Inquiry
Reconciling Privacy and Explainability in High-Stakes: A Systematic Inquiry
Supriya Manna
Niladri Sett
177
0
0
30 Dec 2024
Counterfactual Metarules for Local and Global Recourse
Counterfactual Metarules for Local and Global Recourse
Tom Bewley
Salim I. Amoukou
Saumitra Mishra
Daniele Magazzeni
Manuela Veloso
42
1
0
29 May 2024
Fairness in Algorithmic Recourse Through the Lens of Substantive
  Equality of Opportunity
Fairness in Algorithmic Recourse Through the Lens of Substantive Equality of Opportunity
Andrew Bell
Joao Fonseca
Carlo Abrate
Francesco Bonchi
Julia Stoyanovich
FaML
33
2
0
29 Jan 2024
Confident Feature Ranking
Confident Feature Ranking
Bitya Neuhof
Y. Benjamini
FAtt
34
3
0
28 Jul 2023
GLOBE-CE: A Translation-Based Approach for Global Counterfactual
  Explanations
GLOBE-CE: A Translation-Based Approach for Global Counterfactual Explanations
Dan Ley
Saumitra Mishra
Daniele Magazzeni
LRM
38
16
0
26 May 2023
Generating robust counterfactual explanations
Generating robust counterfactual explanations
Victor Guyomard
Franccoise Fessant
Thomas Guyet
Tassadit Bouadi
Alexandre Termier
46
10
0
24 Apr 2023
"How to make them stay?" -- Diverse Counterfactual Explanations of
  Employee Attrition
"How to make them stay?" -- Diverse Counterfactual Explanations of Employee Attrition
André Artelt
Andreas Gregoriades
31
5
0
08 Mar 2023
CLEAR: Generative Counterfactual Explanations on Graphs
CLEAR: Generative Counterfactual Explanations on Graphs
Jing Ma
Ruocheng Guo
Saumitra Mishra
Aidong Zhang
Jundong Li
CML
OOD
40
54
0
16 Oct 2022
RESHAPE: Explaining Accounting Anomalies in Financial Statement Audits
  by enhancing SHapley Additive exPlanations
RESHAPE: Explaining Accounting Anomalies in Financial Statement Audits by enhancing SHapley Additive exPlanations
Ricardo Müller
Marco Schreyer
Timur Sattarov
Damian Borth
AAML
MLAU
35
7
0
19 Sep 2022
Explainable AI for clinical and remote health applications: a survey on
  tabular and time series data
Explainable AI for clinical and remote health applications: a survey on tabular and time series data
Flavio Di Martino
Franca Delmastro
AI4TS
30
91
0
14 Sep 2022
Robust Counterfactual Explanations for Tree-Based Ensembles
Robust Counterfactual Explanations for Tree-Based Ensembles
Sanghamitra Dutta
Jason Long
Saumitra Mishra
Cecilia Tilli
Daniele Magazzeni
18
52
0
06 Jul 2022
Consistent Counterfactuals for Deep Models
Consistent Counterfactuals for Deep Models
Emily Black
Zifan Wang
Matt Fredrikson
Anupam Datta
BDL
OffRL
OOD
55
43
0
06 Oct 2021
A Causal Perspective on Meaningful and Robust Algorithmic Recourse
A Causal Perspective on Meaningful and Robust Algorithmic Recourse
Gunnar Konig
Timo Freiesleben
Moritz Grosse-Wentrup
43
16
0
16 Jul 2021
Counterfactual Explanations and Algorithmic Recourses for Machine
  Learning: A Review
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review
Sahil Verma
Varich Boonsanong
Minh Hoang
Keegan E. Hines
John P. Dickerson
Chirag Shah
CML
26
162
0
20 Oct 2020
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
234
2,238
0
24 Jun 2017
1