1. Bayesian Machine Learning
- Posterior inference
2. Bayesian Deep Learning
- How: Variational inference
- Markov Chain Monte Carlo (MCMC) Sampling
- Bayes by Backprop
3. Bayesian Approximation
4. Appolication) Meta-learning: Neural Processes
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