To Predict or to Reject: Causal Effect Estimation with Uncertainty on Networked Data
Author:
Affiliation:
1. The University of Queensland,Australia
2. Health and Wellbeing Queensland,Australia
3. University of Electronic Science and Technology of China,China
Funder
Australian Research Council
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10415628/10415561/10415750.pdf?arnumber=10415750
Reference18 articles.
1. Learning Individual Causal Effects from Networked Observational Data
2. Quantifying ignorance in individual-level causal-effect estimates under hidden confounding;Jesson
3. Identifying causal-effect inference failure with uncertainty-aware models;Jesson;In NIPS,2020
4. On feature collapse and deep kernel learning for single forward pass uncertainty;van Amersfoort;arXiv preprint arXiv:2102.11409,2021
5. Invertible residual networks;Behrmann;ICML,2019
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