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Models/CAE

CAE

Reported on 8 benchmarks across 4 tasks · 2 papers · 8 SOTA

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

Methodology5 results

General ClassificationonMice Protein
Accuracy· 2019-01-27
13.4
SOTA
Concrete Autoencoders for Differentiable Feature Selection and Reconstruction arXiv:1901.09346
General ClassificationonISOLET
Accuracy· 2019-01-27
68.5
SOTA
Concrete Autoencoders for Differentiable Feature Selection and Reconstruction arXiv:1901.09346
General ClassificationonFashion-MNIST
Accuracy· 2019-01-27
67.7
SOTA
Concrete Autoencoders for Differentiable Feature Selection and Reconstruction arXiv:1901.09346
General ClassificationonMNIST
Accuracy· 2019-01-27
90.6
SOTA
Concrete Autoencoders for Differentiable Feature Selection and Reconstruction arXiv:1901.09346
General ClassificationonActivity
Accuracy· 2019-01-27
42
SOTA
Concrete Autoencoders for Differentiable Feature Selection and Reconstruction arXiv:1901.09346

Adversarial1 result

Text GenerationonYelp Review Dataset (Small)
G-Score (BLEU, Accuracy)· 2017-05-26
38.66
best: 74.56 (SAE+Discriminator)
SOTA
Style Transfer from Non-Parallel Text by Cross-Alignment arXiv:1705.09655

Natural Language Processing1 result

Text Style TransferonYelp Review Dataset (Small)
G-Score (BLEU, Accuracy)· 2017-05-26
38.66
best: 74.56 (SAE+Discriminator)
SOTA
Style Transfer from Non-Parallel Text by Cross-Alignment arXiv:1705.09655

Audio1 result

2D Semantic SegmentationonYelp Review Dataset (Small)
G-Score (BLEU, Accuracy)· 2017-05-26
38.66
best: 74.56 (SAE+Discriminator)
SOTA
Style Transfer from Non-Parallel Text by Cross-Alignment arXiv:1705.09655