A Transformer is a type of deep learning architecture that uses an attention mechanism to process text sequences. Unlike traditional models based on recurrent neural networks, Transformers do not rely on sequential connections and are able to capture long-term relationships in a text. The way a T...
Transformers are transforming everything in deep learning. All the attention of deep learning is now on "Attention"! http://t.cn/RSrwyml http://t.cn/ROv8Qxy
Transformers are powerful deep learning models that can be used for a wide variety of natural language processing tasks. The transformers package provided by HuggingFace makes it very easy for developers to use state-of-the-art transformers for standard tasks such as sentiment analysis, question-answ...
主要是基于前人 Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization 的分析方法和数据集。 在三个数据集上finetune以后的结果都表明: Vit-B的效果最好。 比 基于CNN的BiT在 更难的样本上(水鸟在陆地,陆鸟在水里) 效果更好。 预先训练...
动画讲CV/BERT: Pre-training of Deep Bidirectional Transformers for Language Un/双语字幕 1816 1 10:40 App 动画讲CV/Swin Transformer讲解 -ViT升级版/双语字幕 1.2万 -- 11:07 App CVPR 2022 Best student paper作者Hansheng Chen自述论文架构 1413 1 8:36 App 组会前抱佛jio/动画讲CV/Positional embe...
我们的论文发现了在时间序列上正确使用transformer的方式,效果超越DLinear和其他formers,欢迎指正:A Time Series is Worth 64 Words: Long-term Forecasting with Transformers 2022-11-29· 美国 回复6 索马里海岸警卫队 大佬,我在我的工业数据集上发现Transformer效果竟然不如1-D CNN和LSTM with attention...
Vision transformersGeneralizationDeep neural networks may be susceptible to learning spurious correlations that hold on average but not in atypical test samples. As with the recent emergence of vision transformer (ViT) models, it remains unexplored how spurious correlations are manifested in such ...
Transformers are Sample-Efficient World Models Vincent Micheli*,Eloi Alonso*,François Fleuret * Denotes equal contribution IRIS agent after 100k environment steps, i.e. two hours of real-time experience tl;dr IRIS is a data-efficient agent trained over millions of imagined trajectories in a worl...
Large language models (LLMs) are deep learning algorithms that can recognize, summarize, translate, predict, and generate content using very large datasets.
Deep Learning is What You Do Not Need by Valeriy Manokhin (2022) 🔥🔥🔥🔥🔥 Why do Transformers suck at Time Series Forecasting by Devansh (2023) Frequency-domain MLPs are More Effective Learners in Time Series Forecasting by Kun Yi, Qi Zhang, Wei Fan, Shoujin Wang, Pengyang Wang...