Examples

This page contains tutorial notebooks for BayesFlow, ranging from toy models to more complex applied modeling scenarios. The corresponding Jupyter Notebooks are available here.

• 1. Diffusion Models In Simulation-Based Inference: A Tutorial
• 2. Bayesian Linear Regression Starter
• 3. Image data: Inference on Spatial Data and Parameters
• 4. Rapid Iteration with Point Estimation - Lotka-Volterra Dynamics
• 5. Simple Model Comparison - One Sample T-Test
• 6. From ABC to BayesFlow
• 7. Posterior Estimation for SIR-like Models
• 8. Bayesian Experimental Design (BED) with BayesFlow and PyTorch
• 9. Likelihood Estimation
• 10. Posterior Estimation With Multimodal Data
• 11. Ensembles
• 12. Neural Likelihood-to-Evidence Ratio Estimation