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Explaining the Behavior of Black-Box Prediction Algorithms with Causal Learning

Explaining the Behavior of Black-Box Prediction Algorithms with Causal Learning

10 January 2025
Numair Sani
Daniel Malinsky
I. Shpitser
    CML
ArXivPDFHTML

Papers citing "Explaining the Behavior of Black-Box Prediction Algorithms with Causal Learning"

11 / 11 papers shown
Title
I Bet You Did Not Mean That: Testing Semantic Importance via Betting
I Bet You Did Not Mean That: Testing Semantic Importance via Betting
Jacopo Teneggi
Jeremias Sulam
FAtt
23
1
0
29 May 2024
DiConStruct: Causal Concept-based Explanations through Black-Box
  Distillation
DiConStruct: Causal Concept-based Explanations through Black-Box Distillation
Ricardo Moreira
Jacopo Bono
Mário Cardoso
Pedro Saleiro
Mário A. T. Figueiredo
P. Bizarro
CML
11
4
0
16 Jan 2024
Beyond Single-Feature Importance with ICECREAM
Beyond Single-Feature Importance with ICECREAM
M.-J. Oesterle
Patrick Blobaum
Atalanti A. Mastakouri
Elke Kirschbaum
CML
22
1
0
19 Jul 2023
PWSHAP: A Path-Wise Explanation Model for Targeted Variables
PWSHAP: A Path-Wise Explanation Model for Targeted Variables
Lucile Ter-Minassian
Oscar Clivio
Karla Diaz-Ordaz
R. Evans
Chris Holmes
14
1
0
26 Jun 2023
Causal Dependence Plots
Causal Dependence Plots
Joshua R. Loftus
Lucius E.J. Bynum
Sakina Hansen
CML
28
1
0
07 Mar 2023
Explaining Image Classifiers Using Contrastive Counterfactuals in
  Generative Latent Spaces
Explaining Image Classifiers Using Contrastive Counterfactuals in Generative Latent Spaces
Kamran Alipour
Aditya Lahiri
Ehsan Adeli
Babak Salimi
M. Pazzani
CML
11
7
0
10 Jun 2022
DagSim: Combining DAG-based model structure with unconstrained data
  types and relations for flexible, transparent, and modularized data
  simulation
DagSim: Combining DAG-based model structure with unconstrained data types and relations for flexible, transparent, and modularized data simulation
Ghadi S. Al Hajj
J. Pensar
G. K. Sandve
CML
AI4CE
14
4
0
06 May 2022
Sequentially learning the topological ordering of causal directed
  acyclic graphs with likelihood ratio scores
Sequentially learning the topological ordering of causal directed acyclic graphs with likelihood ratio scores
Gabriel Ruiz
Oscar Hernan Madrid Padilla
Qing Zhou
CML
6
2
0
03 Feb 2022
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery
M. Vowels
Necati Cihan Camgöz
Richard Bowden
CML
11
294
0
03 Mar 2021
BRPO: Batch Residual Policy Optimization
BRPO: Batch Residual Policy Optimization
Kentaro Kanamori
Yinlam Chow
Takuya Takagi
Hiroki Arimura
Honglak Lee
Ken Kobayashi
Craig Boutilier
OffRL
131
46
0
08 Feb 2020
On Completeness-aware Concept-Based Explanations in Deep Neural Networks
On Completeness-aware Concept-Based Explanations in Deep Neural Networks
Chih-Kuan Yeh
Been Kim
Sercan Ö. Arik
Chun-Liang Li
Tomas Pfister
Pradeep Ravikumar
FAtt
120
297
0
17 Oct 2019
1