还是先回顾一下patch的具体操作,是把一条序列切分成片段,然后按照片段进行建模。好处在于:1、保留更长的前后信息;2、节约transformer计算成本。 那原始的patch是否有不足呢?有的,首先原始patch是对所有的数据集按照相同的片段长度进行切分。但实际情况是不同数据集的采样频率有巨大差距。如下图所示,像汇率数据集、疾...
先看下面的图,Transformer是点编码,Itransformer是编码整条序列,Patch TST则是切片。可以看到原始Transformer是通道依赖,而iTransformer和PatchTST则是通道独立。 与已有的模型不同,本文则是通道依赖,而且作者设计了一种多粒度patch切分方法,把从L1-Ln的长度全部切分了一遍,文章称之为跨通道多粒度patch嵌入,在此基础上...
之前讲过,放回到LSTM、Transformer时,数据还是要变回三维,因此这里我们把batch和channel合并到一起,数据维度变成了:[(bs*ch), pnum, plen] 此时已经可以放入到模型建模,LSTM输出结果的维度是:[(bs*ch), plen, hidden],然后我们通过线性层和reshape操作,把维度调整回[(bs,pred_len, ch] 代码如下,其实就是维度...
Recently, Transformer-based video recognition models have achieved state-of-the-art results on major video recognition benchmarks. However, their high inference cost significantly limits research speed and practical use. In video compression, methods considering small motions and residuals that are...
在本文中,我们探讨了针对视觉Transformer的基于决策的黑盒对抗攻击。鉴于ViT不同patch之间噪声敏感性存在较大差异,我们提出了逐patch的噪声去除方法PAR以提升决策攻击的查询效率。PAR同时维护噪声幅度和噪声敏感性掩膜,以逐patch的方式探测和压...
The base model uses a ViT-L/14 Transformer architecture as an image encoder and uses a masked self-attention Transformer as a text encoder. These encoders are trained to maximize the similarity of (image, text) pairs via a contrastive loss. ...
CD Projekt RED states that the Transformer model enhances visual stability, lighting, and detail during motion, resulting in a clearer and more detailed visual experience. This option allows players to adjust their graphical settings based on their hardware capabilities and performance pref...
Visual language pre-training (VLP) models have demonstrated significant success in various domains, but they remain vulnerable to adversarial attacks. Addressing these adversarial vulnerabilities is crucial for enhancing security in multi-modal learning. Traditionally, adversarial methods that target VLP model...
WFTNET: EXPLOITING GLOBAL AND LOCAL PERIODICITY IN LONG-TERM TIME SERIES FORECASTING 论文链接:arxiv.org/pdf/2309.1131 最近的CNN和Transformer-based模型尝试利用频率和周期性信息进行长期时间序列预测。然而,大多数现有的工作是基于傅里叶变换,无法捕捉细粒度和局部频率结构。在本文中,我们提出了一种Wavelet-Fourier...
It also outperforms the latest strong benchmarks of Patch-Transformer models (by 1-2%) with a significant reduction in memory and runtime (2-3X). For more details, refer to the paper. In this blog, we will demonstrate examples of getting started with PatchTSMixer. We will first ...