Semi-Modular Inference: enhanced learning in multi-modular models by tempering the influence of components
Bayesian statistical inference loses predictive optimality when generative models are misspecified. Working within an existing coherent loss-based generalisation of Bayesian inference, we show existing Modular/Cut-model inference is coherent, and write down a new family of Semi-Modular Inference (...
| Main Authors: | , |
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| Format: | Conference item |
| Language: | English |
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Proceedings of the Machine Learning Research
2021
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