Variational Bayesian Methods for Inferring Spatial Statistics and Nonlinear Dynamics
This thesis discusses four novel statistical methods and approximate inference techniques for analyzing structured neural and molecular sequence data. The main contributions are new algorithms for approximate inference and learning in Bayesian latent variable models involving spatial statistics and...
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| Language: | English |
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2021
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| Online Access: | https://doi.org/10.7916/d8-tk49-d623 |