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IEEE short course

P1.1 - Introduction I
01 Feb 2024

P1.1 - Introduction I

1.00 pdh 0.10 ceu
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P5.13-Variational Inference and Linear Regression
01 Feb 2024

P5.13-Variational Inference and Linear Regression

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P5.12-The Variational Approximation Method
01 Feb 2024

P5.12-The Variational Approximation Method

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P5.11-Exponential Family of Distributions
01 Feb 2024

P5.11-Exponential Family of Distributions

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P5.10-A Lower Bound Interpretation of EM
01 Feb 2024

P5.10-A Lower Bound Interpretation of EM

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P5.9-Clustering, GMMs and the k-Means Algorithm
01 Feb 2024

P5.9-Clustering, GMMs and the k-Means Algorithm

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P5.8-Gaussian Mixture Models
01 Feb 2024

P5.8-Gaussian Mixture Models

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P5.7-The EM and the Linear Regression Task
01 Feb 2024

P5.7-The EM and the Linear Regression Task

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P5.6-The EM Algorithm
01 Feb 2024

P5.6-The EM Algorithm

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P5.5-The Evidence Function
01 Feb 2024

P5.5-The Evidence Function

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P5.4-Bayesian Regression-Simulation Examples
01 Feb 2024

P5.4-Bayesian Regression-Simulation Examples

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P5.3-Bayesian Generalized Linear Regression
01 Feb 2024

P5.3-Bayesian Generalized Linear Regression

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