Unrecorded-weight vision models in 2016
13
Models
11 organisations
—
Open weights
0 open, 0 closed
2
Frontier
By Epoch's flag
23M
Largest traceable
Xception
2016
Span
2 with a traceable size
Releases
by monthOrganisation
Records
13| Model | Organisation | Released | Parameters | Weights |
|---|---|---|---|---|
| Elastic weight consolidation | DeepMind | 2016-12 | — | Not recorded |
| Image-to-image cGAN | University of California (UC) Berkeley | 2016-11 | — | Not recorded |
| NASv3 (CIFAR-10) | Google Brain | 2016-11 | 37M * | Not recorded |
| PolyNet | Chinese University of Hong Kong (CUHK) | 2016-11 | 92M * | Not recorded |
| Xception | 2016-10 | 23M | Not recorded | |
| ResNet-1001 | Microsoft | 2016-09 | 10M * | Not recorded |
| Wide Residual Network | Université Paris-Est | 2016-09 | — | Not recorded |
| SimpleNet | Sensifai | 2016-08 | 5M | Not recorded |
| PixelCNN | Google DeepMind | 2016-06 | — | Not recorded |
| R-FCN | Tsinghua University | 2016-06 | — | Not recorded |
| Inception-ResNet-V2 | 2016-02 | 56M * | Not recorded | |
| Inceptionv4 | 2016-02 | 43M * | Not recorded | |
| SqueezeNet | DeepScale | 2016-02 | 1M * | Not recorded |
An asterisk marks a parameter figure the source does not consider traceable to the people who built the model. That judgement is the source’s and it has false negatives: Kimi K3 is marked speculative at 2.8T while Moonshot’s own model card states the figure. Why that distinction carries the whole exhibit.
Counts are of models Epoch AI records as notable, not of every model released. The most recent month is always incomplete, because a model enters the dataset when it is reviewed rather than when it ships.
Epoch AI, 'Data on AI Models'. Published online at epoch.ai. Retrieved from 'https://epoch.ai/data/ai-models-documentation' Used under CC BY 4.0.