Train with 1000
Ranking
| Accuracy ▼ | Cross entropy ▼ | Name ▼ | Code ▼ | Date ▼ | Paper ▼ |
|---|---|---|---|---|---|
| 0.1676 | 4.5486 | Train1000 wig ensemble | https://github.com/m... | 2018/11/15 | [01] |
| 0.0967 | 6.6217 | Train1000 sample | https://github.com/m... | 2018/11/09 |
| [01] | M. Tanaka, Weighted Sigmoid Gate Unit for an Activation Function of Deep Neural Network, arXiv preprint arXiv:1810.01829, 2018. |
Reference code
The reference code is here, which includes obtaining 1,000 samples and sample network training for each dataset.
 Python |
 matlab |
Submission
Please submit your results of train with 1000!
Links
- Twitter hash tag: #train1000
- My personal page
- My research page
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