Kohonen network
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
- Helsinki University of Technology
- Organisation type
- Academia
- Country
- Finland
- Published
- 25 July 1981
- Authors
- T Kohonen
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Mathematics
- Task
- Dimensionality reduction
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.
- Parameters
- 4.1K
- Training data
- 4,000 tokens
The input vectors are 3D. I could not find the grid size, but from the images it looks 8x8. So the network was 8x8x3 parameters.
??? Seemingly no info
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Why it is tracked
- Highly cited
- Citations
- 11,841
Sources
Where this record came from and when it was last checked.
- Reference
- Self-organized formation of topologically correct feature maps
- Last updated
- 28 November 2025
What the numbers mean
About this model
Kohonen network was published by Helsinki University of Technology, in the country recorded as Finland, during July 1981. It comes out of an organisation categorised as academia.
It works in the domain of Mathematics, and is recorded as performing the task of dimensionality reduction.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Training and provenance
Training consumed a corpus of around 4,000 tokens of text.
The reason it appears in this catalogue at all: highly cited.
Answers
Kohonen network — common questions
Kohonen network— what is it used for?
It works in the domain of Mathematics, and is recorded as handling the task of dimensionality reduction. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
Kohonen network— what GPU do I need to run it?
None. This 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.
Kohonen network— is it open source?
The licensing was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
Kohonen network— how many parameters does it have?
It has a parameter count of 4.1K. The input vectors are 3D. I could not find the grid size, but from the images it looks 8x8. So the network was 8x8x3 parameters. That figure is the total, and it is what decides how much memory the model needs — roughly half a gigabyte per billion at the compression most people use.
Kohonen network— who created it?
It was published by Helsinki University of Technology, based in Finland, an organisation categorised as academia.
Kohonen network— when was it released?
It was published in July 1981. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
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.