ExamplesΒΆ
Here are some examples of how to use ProbFlow to build, fit, and diagnose several different types of Bayesian models:
- Linear Regression
- Logistic Regression
- Fully-connected Neural Network
- Poisson Regression (GLM)
- Robust Heteroscedastic Regression
- Censored Time-to-Event Model
- Multivariate Regression
- Neural Linear Model
- Mixed Effects / Multilevel Models
- Autoregressive Models
- Bayesian Correlation
- Gaussian Mixture Model
- Stochastic Volatility Model
- Normalizing Flows
- Probabilistic PCA
- Latent Dirichlet Allocation
- Entity Embeddings
- Neural Matrix Factorization
- Batch Normalization
- Mixture Density Network
- Variational Autoencoder
- Generative Adversarial Network