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In the past two years, there have been numerous papers written on Transformer, and researchers are designing Transformer models for all kinds of tasks. However, is attention, the core module of Transformer, really stronger than convolution? This paper may bring…

Christopher Bishop, Technical Fellow and Director, Microsoft Research AI4Science
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| Christopher Bishop

Editor’s note, Oct. 20, 2023 – The post was updated to remove information related to the Amsterdam lab, as those details have since changed. Over the coming decade, deep learning looks set to have a transformational impact on the natural…

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Addressing and mitigating the effects of climate change requires a collective effort, bringing our strengths to bear across industry, government, academia, and civil society.

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WWW (Proceedings of the ACM Web Conference) is one of the most important international conferences in the field of Internet technology. WWW 2022 was held as an online conference in Lyon, France, on April 25-29. A total of 1,822 long…

On the left, a diagram with three layers, each of which contains a half-transparent image processed from the same image. The processed images are partitioned into several grids, and each grid contains 4 x 4 image patches. From bottom to top, the number of grids in each layer are 4 x 4, 2 x 2, and 1 x 1, respectively. The layers are labeled “4x,” “8x,” and “16x,” respectively, from bottom to top. An arrow joining the three layers points upward to the words “Segmentation” and “Detection” and an ellipsis. Another arrow points from the top layer to the word “classification.” On the right, a bar chart with a blue bar labeled “Swin V1” and an orange bar labeled “Swin V2.” The orange bar is much taller and labeled “3 billion (1,536 x 1,536 resolution)”; the blue bar is labeled “197 million.” An arrow labeled “15x” points upward from the blue bar, indicating the orange bar is 15 times higher than the blue one.
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| Han Hu 和 Baining Guo

Early last year, our research team from the Visual Computing Group (opens in new tab) introduced Swin Transformer (opens in new tab), a Transformer-based general-purpose computer vision architecture that for the first time beat convolutional neural networks on the important…

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新闻报道 | Microsoft Innovation

Learn how Swin Transformer surpasses previously dominant CNN (convolutional neural network) architectures in computer vision. Presented by Han Hu, Principal Researcher and Research Manager from Microsoft Research Asia.

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As a top international academic conference in the field of natural language processing, ACL attracts paper submissions and conference participation from a large number of scholars every year. This year’s ACL conference was held from May 22nd to May 27th.…

A lightbulb-shaped image, set against a background that represents computer circuitry, is divided into seven sections, with a small research-related icon in each section. Moving clockwise from upper right to upper left, the seven icons are a set of scales, a padlock, a badge, two hands clasped in a handshake, a human brain, a group of three people, and a human eye.
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| Shun Zheng, Jiang Bian, Tie-Yan Liu, Li Zhao, Tao Qin, Yue Wang, Dongsheng Li, Yuqing Yang, 和 Xufang Luo

ICLR (International Conference on Learning Representations) (opens in new tab) is recognized as one of the top conferences in the field of deep learning. Many influential papers on artificial intelligence, statistics, and data science—as well as important application fields such…

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新闻报道 | AI – Cognitive Services Blog

Neural Text-to-Speech (Neural TTS), a powerful speech synthesis capability of Azure Cognitive Services, enables users to convert text to lifelike speech. It is used in various scenarios including voice assistant, content read-aloud capabilities, accessibility tools, and more. Azure Neural TTS…