| Autor: |
Kungurtsev, Vyacheslav, Apaar, Khandelwal, Aarya, Rastogi, Parth Sandeep, Chatterjee, Bapi, Mareček, Jakub |
| Rok vydání: |
2024 |
| Předmět: |
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| Druh dokumentu: |
Working Paper |
| Popis: |
In this work, we demonstrate the Empirical Bayes approach to learning a Dynamic Bayesian Network. By starting with several point estimates of structure and weights, we can use a data-driven prior to subsequently obtain a model to quantify uncertainty. This approach uses a recent development of Generalized Variational Inference, and indicates the potential of sampling the uncertainty of a mixture of DAG structures as well as a parameter posterior. |
| Databáze: |
arXiv |
| Externí odkaz: |
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