Local Loss
PyTorch code for training neural networks without global back-propagation
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Random Erasing | 697 | 6 months ago | 11 | apache-2.0 | Python | |||||
| Random Erasing Data Augmentation. Experiments on CIFAR10, CIFAR100 and Fashion-MNIST | ||||||||||
| Tensorflow Mnist Cnn | 171 | 6 years ago | 7 | Python | ||||||
| MNIST classification using Convolutional NeuralNetwork. Various techniques such as data augmentation, dropout, batchnormalization, etc are implemented. | ||||||||||
| Tanda | 157 | 2 years ago | 12 | mit | Python | |||||
| Learning to Compose Domain-Specific Transformations for Data Augmentation | ||||||||||
| Mojo Cnn | 152 | 6 years ago | 5 | mit | C++ | |||||
| mojo cnn: c++ convolutional neural network | ||||||||||
| Swift4tf | 130 | 4 years ago | 1 | Jupyter Notebook | ||||||
| A set of notebooks explaining swift for tensorflow optimized to run in Google Collaboratory. | ||||||||||
| Local Loss | 123 | 5 years ago | 3 | Python | ||||||
| PyTorch code for training neural networks without global back-propagation | ||||||||||
| Ti Pooling | 117 | 7 years ago | other | Python | ||||||
| TI-pooling: transformation-invariant pooling for feature learning in Convolutional Neural Networks | ||||||||||
| How Far Can We Go With Mnist | 59 | 7 years ago | ||||||||
| A collection of codes for 'how far can we go with MNIST' challenge | ||||||||||
| Roteqnet | 43 | 2 years ago | Python | |||||||
| Rotational Equivariant Networks for PyTorch/Python | ||||||||||
| Dec Da | 33 | 5 years ago | 1 | mit | Python | |||||
| Deep Embedded Clustering with Data Augmentation (DEC-DA). Performance on MNIST (acc=0.985, nmi=0.960). | ||||||||||
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