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Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability
Ilya Feige, Colin Rowat, Christopher Frye
Economics
Research output
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Working paper/Preprint
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Working paper
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Dive into the research topics of 'Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability'. Together they form a unique fingerprint.
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Keyphrases
Causal Knowledge
100%
Model Explanation
100%
Explainability
100%
Shapley Value
100%
AI-based Methods
42%
High Performance
14%
Feature Selection
14%
Causal Structure
14%
Time Series Model
14%
AI Models
14%
Value Frameworks
14%
Support Feature
14%
Attribution Methods
14%
Causal Information
14%
Model Retraining
14%
Unfair Discrimination
14%
Policy Articulation
14%
Mathematics
Asymmetric
100%
Shapley Value
100%
Explainability
100%
Time Series Model
14%
Generality
14%
Input Feature
14%
Causal Structure
14%
Computer Science
Artificial Intelligence
100%
Causal Knowledge
100%
Feature Extraction
25%
Feature Selection
25%
Earth and Planetary Sciences
Artificial Intelligence
100%
Time Series
25%
Retraining
25%