Bayesian inference with sources of uncertainty: from confidence modelling to sparse estimation
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866913088608927744 |
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| author | Rosa, Rafael Mouallem Arbel, Julyan Nguyen, Hien Duy |
| author_facet | Rosa, Rafael Mouallem Arbel, Julyan Nguyen, Hien Duy |
| contents | We introduce a general framework that extends Bayesian inference by allowing the researcher to explicitly encode confidence in each source of uncertainty within the model. This mechanism provides a new handle for model design and regularisation control. Building on this framework, we develop a general approach for inducing sparsity in statistical models and illustrate its use in linear and logistic regression, as well as in Bayesian neural networks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_03134 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Bayesian inference with sources of uncertainty: from confidence modelling to sparse estimation Rosa, Rafael Mouallem Arbel, Julyan Nguyen, Hien Duy Methodology Machine Learning 62F15, 62C10, 62J07, 62J12 We introduce a general framework that extends Bayesian inference by allowing the researcher to explicitly encode confidence in each source of uncertainty within the model. This mechanism provides a new handle for model design and regularisation control. Building on this framework, we develop a general approach for inducing sparsity in statistical models and illustrate its use in linear and logistic regression, as well as in Bayesian neural networks. |
| title | Bayesian inference with sources of uncertainty: from confidence modelling to sparse estimation |
| topic | Methodology Machine Learning 62F15, 62C10, 62J07, 62J12 |
| url | https://arxiv.org/abs/2605.03134 |