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Counterfactual Fairness with Disentangled Causal Effect Variational
  Autoencoder

Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder

24 November 2020
Hyemi Kim
Seungjae Shin
Joonho Jang
Kyungwoo Song
Weonyoung Joo
Wanmo Kang
Il-Chul Moon
    BDL
    CML
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Papers citing "Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder"

13 / 13 papers shown
Title
Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models
Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models
Ruta Binkyte
Ivaxi Sheth
Zhijing Jin
Mohammad Havaei
Bernhard Schölkopf
Mario Fritz
158
0
0
28 Feb 2025
Counterfactual Generative Modeling with Variational Causal Inference
Counterfactual Generative Modeling with Variational Causal Inference
Yulun Wu
Louie McConnell
Claudia Iriondo
CML
BDL
24
0
0
16 Oct 2024
Counterfactual Fairness by Combining Factual and Counterfactual Predictions
Counterfactual Fairness by Combining Factual and Counterfactual Predictions
Zeyu Zhou
Tianci Liu
Ruqi Bai
Jing Gao
Murat Kocaoglu
David I. Inouye
49
2
0
03 Sep 2024
Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement
Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement
Wenjing Chang
Kay Liu
Philip S. Yu
Jianjun Yu
59
2
0
03 Jun 2024
Causal Inference for Human-Language Model Collaboration
Causal Inference for Human-Language Model Collaboration
Bohan Zhang
Yixin Wang
Paramveer S. Dhillon
38
2
0
30 Mar 2024
Counterfactual Fairness for Predictions using Generative Adversarial
  Networks
Counterfactual Fairness for Predictions using Generative Adversarial Networks
Yuchen Ma
Dennis Frauen
Valentyn Melnychuk
Stefan Feuerriegel
34
2
0
26 Oct 2023
Travel Demand Forecasting: A Fair AI Approach
Travel Demand Forecasting: A Fair AI Approach
Xiaojian Zhang
Qian Ke
Xilei Zhao
AI4TS
35
3
0
03 Mar 2023
Fair mapping
Fair mapping
Sébastien Gambs
Rosin Claude Ngueveu
42
0
0
01 Sep 2022
Meta-Causal Feature Learning for Out-of-Distribution Generalization
Meta-Causal Feature Learning for Out-of-Distribution Generalization
Yuqing Wang
Xiangxian Li
Zhuang Qi
Jingyu Li
Xuelong Li
Xiangxu Meng
Lei Meng
OOD
OODD
BDL
40
25
0
22 Aug 2022
Disentangled Representation with Causal Constraints for Counterfactual
  Fairness
Disentangled Representation with Causal Constraints for Counterfactual Fairness
Ziqi Xu
Jixue Liu
Debo Cheng
Jiuyong Li
Lin Liu
Ke Wang
FaML
OOD
CML
40
7
0
19 Aug 2022
Deep Multi-Modal Structural Equations For Causal Effect Estimation With
  Unstructured Proxies
Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured Proxies
Shachi Deshpande
Kaiwen Wang
Dhruv Sreenivas
Zheng Li
Volodymyr Kuleshov
CML
SyDa
16
11
0
18 Mar 2022
Latent Space Smoothing for Individually Fair Representations
Latent Space Smoothing for Individually Fair Representations
Momchil Peychev
Anian Ruoss
Mislav Balunović
Maximilian Baader
Martin Vechev
FaML
36
19
0
26 Nov 2021
Modeling Techniques for Machine Learning Fairness: A Survey
Modeling Techniques for Machine Learning Fairness: A Survey
Mingyang Wan
Daochen Zha
Ninghao Liu
Na Zou
SyDa
FaML
30
36
0
04 Nov 2021
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