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Stick-Breaking Variational Autoencoders

arXiv 1605.06197 ↗First posted 20 May 2016stat.MLcited by 44

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Abstract (arXiv)

We extend Stochastic Gradient Variational Bayes to perform posterior inference for the weights of Stick-Breaking processes. This development allows us to define a Stick-Breaking Variational Autoencoder (SB-VAE), a Bayesian nonparametric version of the variational autoencoder that has a latent representation with stochastic dimensionality. We experimentally demonstrate that the SB-VAE, and a semi-supervised variant, learn highly discriminative latent representations that often outperform the Gaussian VAE's.

Key facts. Cited by 44 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 May 2016.

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Citing papers per year: 2021: 15; 2022: 7; 2023: 6; 2024: 5; 2025: 7; 2026: 4.

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  2. 2021Priors in Bayesian Deep Learning: A Reviewcited by 101
  3. 2021PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Priorcited by 78
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  7. 2023t3-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergencecited by 17
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  9. 2022Amortized Variational Inference: A Systematic Reviewcited by 16
  10. 2021Cauchy-Schwarz Regularized Autoencodercited by 13
  11. 2022Concept Graph Neural Networks for Surgical Video Understandingcited by 13
  12. 2021Model Selection for Bayesian Autoencoderscited by 10
32 more
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  5. 2022Bayesian Nonparametrics for Offline Skill Discoverycited by 5
  6. 2024A Non-negative VAE:the Generalized Gamma Belief Networkcited by 4
  7. 2021Variational Bayesian Sequence-to-Sequence Networks for Memory-Efficient Sign Language Translationcited by 3
  8. 2024Stabilizing the Kumaraswamy Distributioncited by 3
  9. 2021ByPE-VAE: Bayesian Pseudocoresets Exemplar VAEcited by 2
  10. 2024On Kernel-based Variational Autoencodercited by 2
  11. 2025BN-Pool: Bayesian Nonparametric Pooling for Graphscited by 2
  12. 2021Meta-learning representations for clustering with infinite Gaussian mixture modelscited by 1
  13. 2021Variational Auto Encoder Gradient Clusteringcited by 1
  14. 2021Unsupervised Image Generation with Infinite Generative Adversarial Networkscited by 1
  15. 2023DIVA: A Dirichlet Process Mixtures Based Incremental Deep Clustering Algorithm via Variational Auto-Encodercited by 1
  16. 2023A Metalearned Neural Circuit for Nonparametric Bayesian Inferencecited by 1
  17. 2023ClusterDDPM: An EM clustering framework with Denoising Diffusion Probabilistic Modelscited by 1
  18. 2024The VampPrior Mixture Modelcited by 1
  19. 2025Consistent Amortized Clustering via Generative Flow Networkscited by 1
  20. 2025Robotic Long-Horizon Manipulation with Bayesian Non-parametric Skill Priorscited by 1
  21. 2021Meta-learning Amidst Heterogeneity and Ambiguitycited by 0
  22. 2022A generative recommender system with GMM prior for cancer drug generation and sensitivity predictioncited by 0
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  25. 2025Cloud Model Characteristic Function Auto-Encoder: Integrating Cloud Model Theory with MMD Regularization for Enhanced Generative Modelingcited by 0
  26. 2025Stick-Breaking Mixture Normalizing Flows with Component-Wise Tail Adaptation for Variational Inferencecited by 0
  27. 2025Stick-Breaking Embedded Topic Model with Continuous Optimal Transport for Online Analysis of Document Streamscited by 0
  28. 2025Variational Polya Treecited by 0
  29. 2026Partition of Unity Neural Networks for Interpretable Classification with Explicit Class Regionscited by 0
  30. 2026Metabolic cost of information processing in Poisson variational autoencoderscited by 0
  31. 2026Semantic Novelty at Scale: Narrative Shape Taxonomy and Readership Prediction in 28,606 Bookscited by 0
  32. 2026Knowledge Reutilization in Meta-Reinforcement Learningcited by 0