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| 日期 | 标题 | 封面 | 时长 | 视频（4K） |
| -- | -- | -- | -- | -- |
| 11/29/21 | [ViT](https://arxiv.org/pdf/2010.11929.pdf) 逐段精读 | <img src="imgs/vit.jpg" width="200px"/> | 71:30 | [B站](https://www.bilibili.com/video/BV15P4y137jb/) |
| 11/29/21 | [ViT](https://arxiv.org/pdf/2010.11929.pdf) 逐段精读 | <img src="imgs/vit.jpg" width="200px"/> | 71:30 | [B站](https://www.bilibili.com/video/BV15P4y137jb/), [知乎](https://www.zhihu.com/zvideo/1449195245754380288), [YouTube](https://youtu.be/FRFt3x0bO94) |
| 11/18/21 | [BERT](https://arxiv.org/abs/1810.04805) 逐段精读 | <img src="imgs/bert.jpg" width="200px"/> | 45:49 | [B站](https://www.bilibili.com/video/BV1PL411M7eQ), [知乎](https://www.zhihu.com/zvideo/1445340200976785408), [YouTube](https://youtu.be/ULD3uIb2MHQ) |
| 11/9/21 | [GAN](https://papers.nips.cc/paper/2014/file/5ca3e9b122f61f8f06494c97b1afccf3-Paper.pdf) 逐段精读 | <img src="imgs/gan.jpg" width="200px"/> | 46:16 | [B站](https://www.bilibili.com/video/BV1rb4y187vD/), [知乎](https://www.zhihu.com/zvideo/1442091389241159681), [YouTube](https://www.youtube.com/watch?v=g_0HtlrLiDo) |
| 11/3/21 | 零基础多图详解 [图神经网络](https://distill.pub/2021/gnn-intro/)（GNN/GCN） | <img src="imgs/gnn.jpg" width="200px"/> | 66:19 | [B站](https://www.bilibili.com/video/BV1iT4y1d7zP/), [知乎](https://www.zhihu.com/zvideo/1439540657619087360), [YouTube](https://youtu.be/sejA2PtCITw) |
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| 已录制 | 年份 | 名字 | 简介 | 引用 |
| ------ | ---- | ------------------------------------------------------------ | -------------------- | -----------------------------------------------------------: |
| | 2020 | [ViT](https://arxiv.org/pdf/2010.11929.pdf) | Transformer杀入CV界 | 1527 ([link](https://www.semanticscholar.org/paper/An-Image-is-Worth-16x16-Words%3A-Transformers-for-at-Dosovitskiy-Beyer/7b15fa1b8d413fbe14ef7a97f651f47f5aff3903)) |
| ✅ | 2020 | [ViT](https://arxiv.org/pdf/2010.11929.pdf) | Transformer杀入CV界 | 1527 ([link](https://www.semanticscholar.org/paper/An-Image-is-Worth-16x16-Words%3A-Transformers-for-at-Dosovitskiy-Beyer/7b15fa1b8d413fbe14ef7a97f651f47f5aff3903)) |
| | 2021 | [CLIP](https://openai.com/blog/clip/) | 图片和文本之间的对比学习 | 399 ([link](https://www.semanticscholar.org/paper/Learning-Transferable-Visual-Models-From-Natural-Radford-Kim/6f870f7f02a8c59c3e23f407f3ef00dd1dcf8fc4)) |
| | 2021 | [Swin Transformer](https://arxiv.org/pdf/2103.14030.pdf) | 多层次的Vision Transformer | 384 ([link](https://www.semanticscholar.org/paper/Swin-Transformer%3A-Hierarchical-Vision-Transformer-Liu-Lin/c8b25fab5608c3e033d34b4483ec47e68ba109b7)) |
| | 2021 | [MLP-Mixer](https://arxiv.org/pdf/2105.01601.pdf) | 使用MLP替换self-attention | 137 ([link](https://www.semanticscholar.org/paper/MLP-Mixer%3A-An-all-MLP-Architecture-for-Vision-Tolstikhin-Houlsby/2def61f556f9a5576ace08911496b7c7e4f970a4)) |