🎳 Score-Based Models

Score-based models model the data distribution by seeking to learn its score,

This allows us to capture an extremely broad class of distributions indirectly and avoid the intractable partition problem that many other models face.

To train a model, we can use 🎼 Score Matching. We can then sample from our distribution using ☄️ Langevin Dynamics, which only requires the score function.