mlsanityData to 7 Oct 2026

Conjugate Energy-Based Models

arXiv 2106.13798 ↗First posted 25 Jun 2021cs.LG stat.MLcited by 2

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Abstract (arXiv)

In this paper, we propose conjugate energy-based models (CEBMs), a new class of energy-based models that define a joint density over data and latent variables. The joint density of a CEBM decomposes into an intractable distribution over data and a tractable posterior over latent variables. CEBMs have similar use cases as variational autoencoders, in the sense that they learn an unsupervised mapping from data to latent variables. However, these models omit a generator network, which allows them to learn more flexible notions of similarity between data points. Our experiments demonstrate that conjugate EBMs achieve competitive results in terms of image modelling, predictive power of latent space, and out-of-domain detection on a variety of datasets.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 29 of its 61 references that are in the map. First posted on arXiv 25 Jun 2021.

Builds on

29 of 61 references.

References · 29

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17 more
  1. 2019Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Modelcited by 147
  2. 2018Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objectscited by 128
  3. 2019On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Modelscited by 105
  4. 2020Learning Latent Space Energy-Based Prior Modelcited by 104
  5. 2019Flow Contrastive Estimation of Energy-Based Modelscited by 75
  6. 2020Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Samplingcited by 71
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  12. 2019Exploiting Spatial Invariance for Scalable Unsupervised Object Trackingcited by 40
  13. 2018Divergence Triangle for Joint Training of Generator Model, Energy-based Model, and Inference Modelcited by 34
  14. 2020Joint Training of Variational Auto-Encoder and Latent Energy-Based Modelcited by 30
  15. 2020Hybrid Discriminative-Generative Training via Contrastive Learningcited by 24
  16. 2020Bi-level Score Matching for Learning Energy-based Latent Variable Modelscited by 10
  17. 2019Amortized Population Gibbs Samplers with Neural Sufficient Statisticscited by 6

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Citing papers per year: 2023: 2.

2 papers.

  1. 2023Guiding Energy-based Models via Contrastive Latent Variablescited by 17
  2. 2023Morse Neural Networks for Uncertainty Quantificationcited by 4