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Influential Machine Learning Papers
Basics
"Points of Significance"
2021 Papers
Influential Machine Learning Papers
Dropout | one minute summary
Dropout | one minute summary
A regularization strategy motivated by a theory of the role of sex in evolution
Jeffrey Boschman
Jul 14, 2021
Vision Transformers | one minute summary
Vision Transformers | one minute summary
New idiom: “An Image is Worth 16x16 Pixels”
Jeffrey Boschman
Jul 8, 2021
BERT (Bidirectional Encoder Representations from Transformers) | one minute summary
BERT (Bidirectional Encoder Representations from Transformers) | one minute summary
It took the Transformer, and transformed it to make it even more useful
Jeffrey Boschman
Jul 7, 2021
Batch Normalization | one minute summary
Batch Normalization | one minute summary
Batch norm has become the norm
Jeffrey Boschman
Jul 1, 2021
VGG16 (2014) | one minute summary
VGG16 (2014) | one minute summary
The original super deep ConvNet
Jeffrey Boschman
Jun 24, 2021
Inception-v1 / GoogLeNet (2014) | one minute summary
Inception-v1 / GoogLeNet (2014) | one minute summary
Machine learning inspired by the “we need to go deeper” meme
Jeffrey Boschman
Jun 16, 2021
Domain-Adversarial Training of Neural Networks (2016) | one minute summary
Domain-Adversarial Training of Neural Networks (2016) | one minute summary
DANN, that’s good.
Jeffrey Boschman
May 21, 2021
ResNet (2015) | one minute summary
ResNet (2015) | one minute summary
ResNets remain extremely relevant after 5.5 years
Jeffrey Boschman
May 15, 2021
Transformers (2017) | one minute summary
Transformers (2017) | one minute summary
This paper Transformed the way we think about attention
Jeffrey Boschman
May 5, 2021
Attention (2014) | one minute summary
Attention (2014) | one minute summary
Did you pay attention when this architecture was introduced?
Jeffrey Boschman
May 3, 2021
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