Image Clustering on Fashion-MNIST

Metric: NMI (higher is better)

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#	Model↕	NMI▼	Extra Data	Paper	Date↕	Code
1	PRCut (DinoV2)	0.758	No	-	-	Code
2	SPC	0.735	No	Selective Pseudo-label Clustering	2021-07-22	Code
3	VMM	0.71	No	The VampPrior Mixture Model	2024-02-06	Code
4	DEN	0.71	No	Interpretable Visualizations with Differentiatin...	2020-06-11	Code
5	N2D (UMAP)	0.684	No	N2D: (Not Too) Deep Clustering via Clustering th...	2019-08-16	Code
6	DDC	0.682	No	Deep Density-based Image Clustering	2018-12-11	Code
7	DDC-DA	0.661	No	Deep Density-based Image Clustering	2018-12-11	Code
8	GDL	0.66	No	Graph Degree Linkage: Agglomerative Clustering o...	2012-08-25	Code
9	PSSC	0.644	No	Scattering Transform Based Image Clustering usin...	2020-11-23	Code
10	DynAE	0.642	No	Deep Clustering with a Dynamic Autoencoder: From...	2019-01-23	Code
11	DTI-Clustering	0.637	No	Deep Transformation-Invariant Clustering	2020-06-19	Code
12	SNNL-4	0.574	No	Improving k-Means Clustering Performance with Di...	2020-06-05	Code

#1PRCut (DinoV2)
0.758
NMI
No paperCode
#2SPCSOTA
0.735
NMI· 2021-07-22
Selective Pseudo-label Clustering Code
#3VMM
0.71
NMI· 2024-02-06
The VampPrior Mixture Model Code
#4DENSOTA
0.71
NMI· 2020-06-11
Interpretable Visualizations with Differentiating Embedding Networks Code
#5N2D (UMAP)SOTA
0.684
NMI· 2019-08-16
N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding Code
#6DDCSOTA
0.682
NMI· 2018-12-11
Deep Density-based Image Clustering Code
#7DDC-DA
0.661
NMI· 2018-12-11
Deep Density-based Image Clustering Code
#8GDLSOTA
0.66
NMI· 2012-08-25
Graph Degree Linkage: Agglomerative Clustering on a Directed Graph Code
#9PSSC
0.644
NMI· 2020-11-23
Scattering Transform Based Image Clustering using Projection onto Orthogonal Complement Code
#10DynAE
0.642
NMI· 2019-01-23
Deep Clustering with a Dynamic Autoencoder: From Reconstruction towards Centroids Construction Code
#11DTI-Clustering
0.637
NMI· 2020-06-19
Deep Transformation-Invariant Clustering Code
#12SNNL-4
0.574
NMI· 2020-06-05
Improving k-Means Clustering Performance with Disentangled Internal Representations Code