An approximate sampler for energy-based models with divergence diagnostics

By Bryan Eikema. 2022

11 citations recorded by the source corpus.

Subfields: Generative Models

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In Generative Models

1. Tomasz Korbak
2. Germán Kruszewski
3. Marc Dymetman
4. Jos Rozen
5. Nahyeon Ryu
6. Dongyoung Go

Citations in the corpus

• Aligning Language Models with Preferences through f-divergence Minimization (2023, methodology): “…such as rejection sampling to sample from simple distributions like pGDC bin (Roller et al., 2021; Ziegler et al., 2022), and Quasi Rejection Sampling (QRS) (Eikema et al., 2022) or MCMC techniques (Miao et al., 2019; Goyal et al., 2022) to sample from more complex distributions, such as pGDC dist.”