Causality-Aware Predictions in Static Anticausal Machine Learning Tasks.
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DOI: 10.1109/tnnls.2022.3202151
Abstract: We propose a counterfactual approach to train "causality-aware" predictive models that are able to leverage causal information in static anticausal machine learning tasks (i.e., prediction tasks where the outcome influences the inputs). In applications plagued… read more here.
Keywords: static anticausal; machine learning; causality aware; anticausal machine ... See more keywords