arXiv stat.ML
· Papers
A unifying view of contrastive learning, importance sampling, and bridge sampling for energy-based models
arXiv:2604.08116v2 Announce Type: replace-cross Abstract: In the last decades, energy-based models (EBMs) have become an important class of probabilistic models in which a component of the likelihood is intractable and therefore cannot be evaluated explicitly. Consequently, parameter estimation in EBMs is challenging f