Historical Consensus: Preventing Posterior Collapse via Iterative Selection of Gaussian Mixture Priors | ScienceToStartup | ScienceToStartup

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References (20)

[1]

Posterior Collapse as a Phase Transition in Variational Autoencoders

2025Zhen Li, Fangguo Zhang et al.

[2]

Improving disentanglement in variational auto-encoders via feature imbalance-informed dimension weighting

2024Yue Liu, Zhenyao Yu et al.

[3]

Overcoming Posterior Collapse in Variational Autoencoders Via EM-Type Training

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"A novel training method for VAEs that prevents posterior collapse using iterative Gaussian mixture model selection."

Variational Autoencoders•Score: 7•View PDF ↗

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Historical Consensus: Preventing Posterior Collapse via Iterative Selection of Gaussian Mixture Priors

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References (20)

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"A novel training method for VAEs that prevents posterior collapse using iterative Gaussian mixture model selection."

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Historical Consensus: Preventing Posterior Collapse via Iterative Selection of Gaussian Mixture Priors

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References (20)

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"A novel training method for VAEs that prevents posterior collapse using iterative Gaussian mixture model selection."

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