Maxout Networks
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- University of Montreal / Université de Montréal
- Organisation type
- Academia
- Country
- Canada
- Published
- 18 February 2013
- Authors
- Ian J. Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron Courville, Yoshua Bengio
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision
- Task
- Image classification
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Training data
- 604,388 tokens
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Unknown
- Citations
- 2,576
Sources
Where this record came from and when it was last checked.
- Reference
- Maxout Networks
- Last updated
- 28 November 2025
What the numbers mean
Background
Maxout Networks was published by University of Montreal / Université de Montréal, in Canada, in February 2013. academia is the category the publisher falls under.
It works in Vision, and is recorded as doing image classification.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
How it was trained
It was trained on about 604,388 tokens of text.
Answers
Maxout Networks — common questions
Is Maxout Networks open source?
The licensing for Maxout Networks was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
How many parameters does Maxout Networks have?
No parameter count has been published for Maxout Networks, which is why no memory or speed figure appears on this page.
Who created Maxout Networks?
Maxout Networks was published by University of Montreal / Université de Montréal, based in Canada, categorised as academia.
When was Maxout Networks released?
Maxout Networks was published in February 2013. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
What is Maxout Networks used for?
Maxout Networks works in Vision, and is recorded as handling image classification. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
What GPU do I need to run Maxout Networks?
None. Maxout Networks is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.