SNNL-5

Reported on 5 benchmarks across 1 task · 1 paper · 2 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision5 results

Image ClassificationonEMNIST-Balanced
NMI· 2020-06-05
77.6
SOTA
Improving k-Means Clustering Performance with Disentangled Internal Representations arXiv:2006.04535
Image ClassificationonFashion-MNIST
NMI· 2020-06-05
76.2
SOTA
Improving k-Means Clustering Performance with Disentangled Internal Representations arXiv:2006.04535
Image ClassificationonEMNIST-Balanced
Accuracy· 2020-06-05
78.5
best: 91.48 (EMNIST-mobile)
Improving k-Means Clustering Performance with Disentangled Internal Representations arXiv:2006.04535
Image ClassificationonFashion-MNIST
Accuracy· 2020-06-05
84.4
best: 99.06 (pFedBreD_ns_mg)
Improving k-Means Clustering Performance with Disentangled Internal Representations arXiv:2006.04535
Image ClassificationonMNIST
Accuracy· 2020-06-05
95.5
best: 99.87 (Branching/Merging CNN + Homogeneous Vector Capsules)
Improving k-Means Clustering Performance with Disentangled Internal Representations arXiv:2006.04535