paper list
2016: ICML 2016 Unsupervised deep embedding for clustering analysis
2017:
ICCV 2017: Deep clustering via joint convolutional autoencoder embedding and relative entropy minimization
IJCAI 2017: Improved deep embedded clustering with local structure preservation
NIPS 2017: Deep subspace clustering networks
TIP 2017: Structured autoencoders for subspace clustering
Arxiv 2017: Spectralnet: Spectral clustering using deep neural networks
AAAI 2017: Cascade subspace clustering
AAAI 2017: Unsupervised multi-manifold clustering by learning deep representation
ARXIV 2017: Deep unsupervised clustering using mixture of autoencoders
ICCV 2017: Deep adaptive image clustering
2018:
CVPR 2018: Deep adversarial subspace clustering
Arxiv 2018: Deep k-Means: Jointly clustering with -Means and learning representations
CVPR 2018: Deep density clustering of unconstrained faces
ARXIV 2018: Deep discriminative latent space for clustering
AAAI 2018: Deep embedding for determining the number of clusters
ARXIV 2018: Semi-Supervised Clustering with Neural Networks
2019:
AAAI 2019: Clustergan: Latent space clustering in generative adversarial networks
cvpr 2019: Deep spectral clustering using dual autoencoder network
ICCV 2019: Invariant information clustering for unsupervised image classification and segmentation
CVPR 2019: Efficient parameter-free clustering using first neighbor relations
ARXIV 2019: Deep Clustering with a Dynamic Autoencoder: From Reconstruction towards Centroids Construction
CVPR 2019: Balanced self-paced learning for generative adversarial clustering network
PAMI2019: Deep clustering: On the link between discriminative models and k-means
ICCV 2019: Deep comprehensive correlation mining for image clustering
AAAI 2019: Adversarial incomplete multi-view clustering
TKDE 2019: Adaptive self-paced deep clustering with data augmentation
ICDM 2019: Deep embedded cluster tree
IJCAI 2019: Affine equivariant autoencoder
TNNLS 2019: Learning Deep Landmarks for Imbalanced Classification
TNNLS 2019: Deep Clustering With Sample-Assignment Invariance Prior
AAAI 2019: Adversarial graph embedding for ensemble clustering
TNNLS 2019: Dual Adversarial Autoencoders for Clustering
ARXIV 2019: Deep Discriminative Clustering Analysis
AAAI 2019: Deep adversarial multi-view clustering network
TNNLS 2019: A Deep One-Class Neural Network for Anomalous Event Detection in Complex Scenes
NIPS 2019: Spectral Modification of Graphs for Improved Spectral Clustering
NIPS 2019: Copulas as High-Dimensional Generative Models: Vine Copula Autoencoders
NIPS 2019: Learning Representations for Time Series Clustering
ICCV 2019: Deep Clustering by Gaussian Mixture Variational Autoencoders with Graph Embedding
ICCV 2019: Invariant information clustering for unsupervised image classification and segmentation
2020:
PAMI 2020: Self-supervised visual feature learning with deep neural networks: A survey
TNNLS 2020: Deep subspace clustering
TKDE 2020: Joint Deep Multi-View Learning for Image Clustering
ICASSP 2020: K-Autoencoders Deep Clustering
ARXIV 2020: Robust Self-Supervised Convolutional Neural Network for Subspace Clustering and Classification
ARXIV 2020: DHOG: Deep Hierarchical Object Grouping
KDD 2020: Deep Multimodal Clustering with Cross Reconstruction
TIP 2020: Semantic Neighborhood-Aware Deep Facial Expression Recognition
SPL 2020: Deep Clustering With Variational Autoencoder
TIP 2020: Image Clustering via Deep Embedded Dimensionality Reduction and Probability-Based Triplet Loss
Autoencoder-based Deep clustering:
Deep multi-view clustering:
Deep incompleted multi-view clustering:
Deep multi-modal clustering: