Learning discrete diffusion – MH sampling
Published:
Metropolis–Hastings (MH) is a Markov chain Monte Carlo method that repeatedly draws proposals from a simple distribution and updates the current state with an accept/reject rule.
Notes Archive
2026
Thoughts on Generalization in Diffusion Models
Published:
Generalization is the implicit alignment between neural networks and the underlying data distribution, shaped by both data and human perception.