AI models
Variational Lossy Autoencoder (VLAE) MNIST
Published
Mar 4, 2017
Variational Lossy Autoencoder (VLAE) MNIST is an AI model developed by University of California (UC) Berkeley and OpenAI (United States), first published in March 2017. It works in the vision domain, on tasks such as image representation.
Epoch AI has no training-compute estimate for this model.
Access: Unreleased. Its weights are not openly released.
Full record
- Organization
- University of California (UC) Berkeley, OpenAI
- Country of organization
- United States
- Domain
- Vision
- Task
- Image representation
- Model accessibility
- Unreleased
- Open weights
- No
SourceEpoch AI, 'AI Models'. Published online at epoch.ai. Retrieved 2026-07-29 from https://epoch.ai/data/ai-models. Licensed under CC BY 4.0.
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