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Counterfactual Normalization: Proactively Addressing Dataset Shift and
  Improving Reliability Using Causal Mechanisms

Counterfactual Normalization: Proactively Addressing Dataset Shift and Improving Reliability Using Causal Mechanisms

9 August 2018
Adarsh Subbaswamy
Suchi Saria
    OOD
ArXiv (abs)PDFHTML

Papers citing "Counterfactual Normalization: Proactively Addressing Dataset Shift and Improving Reliability Using Causal Mechanisms"

12 / 12 papers shown
Title
Infant Cry Detection Using Causal Temporal Representation
Minghao Fu
Danning Li
Aryan Gadhiya
Benjamin Lambright
Mohamed Alowais
...
Saad El Dine Elletter
Hawau Olamide Toyin
Haiyan Jiang
Kun Zhang
Hanan Aldarmaki
123
0
0
08 Mar 2025
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
OODOODDBDL
95
25
0
22 Aug 2022
Towards Out-Of-Distribution Generalization: A Survey
Towards Out-Of-Distribution Generalization: A Survey
Jiashuo Liu
Zheyan Shen
Yue He
Xingxuan Zhang
Renzhe Xu
Han Yu
Peng Cui
CMLOOD
168
536
0
31 Aug 2021
Counterfactual Invariance to Spurious Correlations: Why and How to Pass
  Stress Tests
Counterfactual Invariance to Spurious Correlations: Why and How to Pass Stress Tests
Victor Veitch
Alexander DÁmour
Steve Yadlowsky
Jacob Eisenstein
OOD
80
93
0
31 May 2021
Causally motivated Shortcut Removal Using Auxiliary Labels
Causally motivated Shortcut Removal Using Auxiliary Labels
Maggie Makar
Ben Packer
D. Moldovan
Davis W. Blalock
Yoni Halpern
Alexander DÁmour
OODCML
74
75
0
13 May 2021
Towards Causal Representation Learning
Towards Causal Representation Learning
Bernhard Schölkopf
Francesco Locatello
Stefan Bauer
Nan Rosemary Ke
Nal Kalchbrenner
Anirudh Goyal
Yoshua Bengio
OODCMLAI4CE
152
322
0
22 Feb 2021
Causality-aware counterfactual confounding adjustment as an alternative
  to linear residualization in anticausal prediction tasks based on linear
  learners
Causality-aware counterfactual confounding adjustment as an alternative to linear residualization in anticausal prediction tasks based on linear learners
E. C. Neto
OODCML
61
6
0
09 Nov 2020
Stable predictions for health related anticausal prediction tasks
  affected by selection biases: the need to deconfound the test set features
Stable predictions for health related anticausal prediction tasks affected by selection biases: the need to deconfound the test set features
E. C. Neto
Phil Snyder
S. Sieberts
L. Omberg
CMLOOD
11
1
0
09 Nov 2020
Evaluating Model Robustness and Stability to Dataset Shift
Evaluating Model Robustness and Stability to Dataset Shift
Adarsh Subbaswamy
R. Adams
Suchi Saria
OOD
65
9
0
28 Oct 2020
Counterfactual Predictions under Runtime Confounding
Counterfactual Predictions under Runtime Confounding
Amanda Coston
Edward H. Kennedy
Alexandra Chouldechova
OODOffRL
59
28
0
30 Jun 2020
Robust Learning with the Hilbert-Schmidt Independence Criterion
Robust Learning with the Hilbert-Schmidt Independence Criterion
D. Greenfeld
Uri Shalit
OOD
128
59
0
01 Oct 2019
Preventing Failures Due to Dataset Shift: Learning Predictive Models
  That Transport
Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport
Adarsh Subbaswamy
Peter F. Schulam
Suchi Saria
OOD
73
20
0
11 Dec 2018
1