虽然图神经网络被用于Pinterest、阿里巴巴和推特的推荐系统,但一个更巧妙的成功案例是Transformer架构,它在NLP(Natural Language Processing ,自然语言处理)世界掀起了一场风暴。 在这篇文章中,我尝试在图神经网络(GNNs)和Transformers之间建立一种联系。我将讨论 ...
据了解,这是首个关于 Transformers 的专题课程。 要说在世界大学公开课中哪些属于精品,斯坦福大学的 CS 课程可谓是榜上有名。这所世界名校先后免费公开了众多课程,有关于自然语言理解的、有关于机器学习的等等。 斯坦福大学的 CS 课程可以说是覆盖范围广 ...
这篇论文来自Yoshua Bengio的实验室,而标题并不起眼「Neural Machine Translation by Jointly Learning to Align and Translate」。 或许很多人都没有听说过这篇论文,但它是NLP中最伟大的里程碑之一,已经被引用了29K次(相比之下,Transformer为77K)。
In the last decade, convolutional neural networks (CNNs) have been the go-to architecture in computer vision, owing to their powerful capability in learning representations from images/videos.
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