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Learning Interpretable Models with Causal Guarantees

Learning Interpretable Models with Causal Guarantees

24 January 2019
Carolyn Kim
Osbert Bastani
    FaML
    OOD
    CML
ArXivPDFHTML

Papers citing "Learning Interpretable Models with Causal Guarantees"

13 / 13 papers shown
Title
Causal Deep Learning
Causal Deep Learning
Jeroen Berrevoets
Krzysztof Kacprzyk
Zhaozhi Qian
M. Schaar
CML
AI4CE
26
25
0
03 Mar 2023
Explainable AI for Bioinformatics: Methods, Tools, and Applications
Explainable AI for Bioinformatics: Methods, Tools, and Applications
Md. Rezaul Karim
Tanhim Islam
Oya Beyan
Christoph Lange
Michael Cochez
Dietrich-Rebholz Schuhmann
Stefan Decker
42
68
0
25 Dec 2022
Navigating causal deep learning
Navigating causal deep learning
Jeroen Berrevoets
Krzysztof Kacprzyk
Zhaozhi Qian
M. Schaar
CML
46
2
0
01 Dec 2022
Benchmarking Heterogeneous Treatment Effect Models through the Lens of
  Interpretability
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability
Jonathan Crabbé
Alicia Curth
Ioana Bica
M. Schaar
CML
50
16
0
16 Jun 2022
Unsupervised Causal Binary Concepts Discovery with VAE for Black-box
  Model Explanation
Unsupervised Causal Binary Concepts Discovery with VAE for Black-box Model Explanation
Thien Q. Tran
Kazuto Fukuchi
Youhei Akimoto
Jun Sakuma
CML
60
10
0
09 Sep 2021
Information-theoretic Evolution of Model Agnostic Global Explanations
Information-theoretic Evolution of Model Agnostic Global Explanations
Sukriti Verma
Nikaash Puri
Piyush B. Gupta
Balaji Krishnamurthy
FAtt
34
0
0
14 May 2021
Robust and Stable Black Box Explanations
Robust and Stable Black Box Explanations
Himabindu Lakkaraju
Nino Arsov
Osbert Bastani
AAML
FAtt
29
84
0
12 Nov 2020
Causal Explanations of Image Misclassifications
Causal Explanations of Image Misclassifications
Yan Min
Miles K. Bennett
CML
18
0
0
28 Jun 2020
Generative causal explanations of black-box classifiers
Generative causal explanations of black-box classifiers
Matthew R. O’Shaughnessy
Gregory H. Canal
Marissa Connor
Mark A. Davenport
Christopher Rozell
CML
37
73
0
24 Jun 2020
Causal Interpretability for Machine Learning -- Problems, Methods and
  Evaluation
Causal Interpretability for Machine Learning -- Problems, Methods and Evaluation
Raha Moraffah
Mansooreh Karami
Ruocheng Guo
A. Raglin
Huan Liu
CML
ELM
XAI
40
214
0
09 Mar 2020
Evaluating Explanation Without Ground Truth in Interpretable Machine
  Learning
Evaluating Explanation Without Ground Truth in Interpretable Machine Learning
Fan Yang
Mengnan Du
Xia Hu
XAI
ELM
32
67
0
16 Jul 2019
Learning Certifiably Optimal Rule Lists for Categorical Data
Learning Certifiably Optimal Rule Lists for Categorical Data
E. Angelino
Nicholas Larus-Stone
Daniel Alabi
Margo Seltzer
Cynthia Rudin
62
195
0
06 Apr 2017
Learning Representations for Counterfactual Inference
Learning Representations for Counterfactual Inference
Fredrik D. Johansson
Uri Shalit
David Sontag
CML
OOD
BDL
236
726
0
12 May 2016
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