Unsupervised Mnist On Mnist
평가 지표
Accuracy
평가 결과
이 벤치마크에서 각 모델의 성능 결과
모델 이름 | 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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