This repo contains demo implementation of the density-fixing training code in PyTorch based on the following paper:
Masanari Mimura, Ryohei Izawa. Density Fixing: Simple yet Effective Regularization Method based on the Class Prior https://arxiv.org/abs/2007.03899
The following table shows the mean test errors w/ and w/o density-fixing regularization.
| Model | Top 1 Error | Top 5 Error |
|---|---|---|
| ResNet-18 | 12.72% | 0.812% |
| ResNet-18 + density fixing (gamma=1) | 12.23% | 0.779% |
The CIFAR-10 reimplementation of density-fixing is adapted from the pytorch-cifar repository by kuangliu.