1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.LG2026★ 1 cited
Local Learning Rules for Out-of-Equilibrium Physical Generative Models
Cyrill Bösch, Geoffrey Roeder, Marc Serra-Garcia +1
We show that the out-of-equilibrium driving protocol of score-based generative models (SGMs) can be learned via local learning rules. The gradient with respect to the parameters of…
cs.LG2024
Generative Marginalization Models
Sulin Liu, Peter J. Ramadge, Ryan P. Adams
We introduce marginalization models (MAMs), a new family of generative models for high-dimensional discrete data. They offer scalable and flexible generative modeling by explicitly…