AI models
Binarized Neural Network (MNIST)
Parameters
37M
Published
Mar 17, 2016
Binarized Neural Network (MNIST) is an AI model developed by Technion - Israel Institute of Technology, Columbia University and University of Montreal / Université de Montréal (Israel, United States and Canada), first published in March 2016. It works in the vision domain, on tasks such as image classification.
Epoch AI has no training-compute estimate for this model. The model has 37,000,000 parameters. It was trained on roughly 60K datapoints.
The reference paper has 3,299 citations. Epoch AI rates the confidence of this record as speculative.
Full record
- Organization
- Technion - Israel Institute of Technology, Columbia University, University of Montreal / Université de Montréal
- Country of organization
- Israel, United States, Canada
- Domain
- Vision
- Task
- Image classification
- Parameters
- 37,000,000
- Dataset size
- 60K
- Citations
- 3,299
- Epoch confidence
- Speculative
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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