NCAM is a hierarchical Bayesian model using neural networks and conjugate Gaussian inference to learn sensor-specific biases for unsupervised multi-source regression, with added conformal prediction for coverage guarantees.
Yaniv Romano, Evan Patterson, and Emmanuel Candes
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Neural Conjugate Aggregation: Identifiable Unsupervised Multi-Sensor Regression under Heterogeneous Sensor Bias
NCAM is a hierarchical Bayesian model using neural networks and conjugate Gaussian inference to learn sensor-specific biases for unsupervised multi-source regression, with added conformal prediction for coverage guarantees.