Here provide a brief guideline of paper reading about deep clustering, to be continute...
| Paper | Conference |
|---|---|
| A Survey of Clustering With Deep Learning: From the Perspective of Network Architecture | ACCESS 2018 |
| Clustering with Deep Learning: Taxonomy and New Methods | Arxiv 2018 |
| Method | Paper | Conference |
|---|---|---|
| DNC | Deep learning with nonparametric clustering | Arxiv 2015 |
| DEC | Unsupervised deep embedding for clustering analysis | ICML 2016 |
| DBC | Discriminatively boosted image clustering with fully convolutional auto-encoders | Arxiv 2017 |
| CCNN | CNN-based joint clustering and representation learning with feature drift compensation for large-scale image data | TMM 2018 |
| IMSAT | Learning discrete representations via information maximizing self-augmented training | Arxiv 2017 |
| JULE | Joint unsupervised learning of deep representations and image clusters | CVPR 2016 |
| DAC | Deep adaptive image clustering | CVPR 2017 |
| SCCNN | Speaker identification and clustering using convolutional neural networks | MLSP 2016 |
| Method | Paper | Conference |
|---|---|---|
| NMMC | Deep learning with nonparametric clustering | Arxiv 2015 |
| UMMC | Unsupervised multi-manifold clustering by learning deep representation | AAAI 2017 |
| Method | Paper | Conference |
|---|---|---|
| DCN | Towards K-means-friendly spaces: Simultaneous deep learning and clustering | Arxiv 2016 |
| DEN | Deep embedding network for clustering | ICPR 2014 |
| DSC-Nets | Deep Subspace Clustering Networks | NIPS 2017 |
| DMC | Unsupervised multi-manifold clustering by learning deep representation | AAAI 2017 |
| DEPICT | Deep clustering via joint convolutional autoencoder embedding and relative entropy minimization | ICCV 2017 |
| DCC | Unsupervised multi-manifold clustering by learning deep representation | AAAI 2017 |
| Method | Paper | Conference |
|---|---|---|
| VaDE | Variational deep embedding: An unsupervised and generative approach to clustering | Arxiv 2016 |
| GMVAE | Deep unsupervised clustering with Gaussian mixture variational autoencoders | Arxiv 2016 |
| Method | Paper | Conference |
|---|---|---|
| DAC | Deep adversarial Gaussian mixture auto-encoder for clustering | ICLR 2017 |
| CatGAN | Unsupervised and semi-supervised learning with categorical generative adversarial networks | Arxiv 2015 |
| InfoGAN | InfoGAN: Interpretable representation learning by information maximizing generative adversarial nets | NIPS 2016 |
| Method | Paper | Conference |
|---|---|---|
| DeepCluster | Deep Clustering for Unsupervised Learning of Visual Features | ECCV 2018 |