Attention Is All You Need
The Transformer replaces recurrent sequence processing with attention, creating a foundation for many later language and multimodal models.
THE RESEARCH ATLAS
ImageNet Classification with Deep Convolutional Neural Networks
A deep convolutional network demonstrated how data, GPU computation and learned representations could transform visual recognition.
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Location refers to credited institutions or the listed organization, not author citizenship or an exhaustive collaboration list.
Why read this
Start here to understand the shift from hand-designed features to learned representations.
Citation
@misc{krizhevsky2012imagenet,
title = {ImageNet Classification with Deep Convolutional Neural Networks},
author = {Alex Krizhevsky and Ilya Sutskever and Geoffrey E. Hinton},
year = {2012},
url = {https://papers.nips.cc/paper_files/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.html}
}Rights remain with the original authors. Refer to the original source for citations and licensing.
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