Train with 1000
Ranking
| Accuracy ▼ | Cross entropy ▼ | Name ▼ | Code ▼ | Date ▼ | Paper ▼ |
|---|---|---|---|---|---|
| 0.8159 | 0.5749 | Train1000 wig ensemble | https://github.com/m... | 2018/11/16 | [01] |
| 0.8152 | 1.3249 | Train1000 sample | https://github.com/m... | 2018/11/16 |
| [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
Copyright© Okutomi-Tanaka Lab All Rights Reserved.