Unsupervised Mnist On Mnist
评估指标
Accuracy
评测结果
各个模型在此基准测试上的表现结果
模型名称 | Accuracy | Paper Title | Repository |
|---|---|---|---|
| SubTab | 98.31 | SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning | - |
| Bidirectional InfoGAN | 96.61 | Inferencing Based on Unsupervised Learning of Disentangled Representations | - |
| Sparse Manifold Transform | 99.3 | Minimalistic Unsupervised Learning with the Sparse Manifold Transform | - |
| SCAE (LIN-MATCH) | 98.7 | Stacked Capsule Autoencoders | - |
| PixelGAN Autoencoders | 94.73 | PixelGAN Autoencoders | - |
| IIC | 99.3 | Invariant Information Clustering for Unsupervised Image Classification and Segmentation | - |
| Adversarial AE | 95.9 | Adversarial Autoencoders | - |
| density based | - | DenMune: Density peak based clustering using mutual nearest neighbors | - |
| InfoGAN | 95 | InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets | - |
| CatGAN | 95.73 | Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks | - |
| Self-Organizing Map | 96.9 | Improving Self-Organizing Maps with Unsupervised Feature Extraction | - |
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