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        • Batch Normalization: Accelerating Deep Network Training b y Reducing Internal Covariate Shift
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      • batch-regularization
        • Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models
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        • DIFFERENTIABLE LEARNING-TO-NORMALIZE VIA SWITCHABLE NORMALIZATION
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        • Instance Normalization: The Missing Ingredient for Fast Stylization
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        • BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Mode
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        • ADAM: A METHOD FOR STOCHASTIC OPTIMIZATION
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      • Implementation
        • 论文复现指南-CV方向
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        • 论文复现赛指南-NLP方向
      • Implementation
        • 论文复现赛指南-推荐方向
      • Implementation
        • 模型工程落地赛指南
      • Implementation
        • 论文复现指南
      • List
        • attention
      • List
        • 神经网络基础(basis)
      • List
        • batch_normalization
      • List
        • 图像分类(CLAS)
      • List
        • convolutional
      • List
        • gan
      • List
        • 论文阅读清单
      • List
        • 论文阅读清单
      • List
        • 大语言模型(Large Language Models)
      • List
        • multimodal
      • List
        • 自然语言处理(NLP)
      • List
        • 目标检测(OBJ)
      • List
        • rnn
      • List
        • segementation
      • List
        • transformer
      • Method
        • 高效阅读方法及流程
      • Method
        • 如何阅读论文
      • Method
        • 论文阅读指南
      • Method
        • 论文速读十问
      • Method
        • 读论文与口头报告的几项重点
      • Method
        • 参考材料
      • Notes
        • 论文阅读术语整理总结
      • Notes
      • Notes
        • Attention
      • Notes
        • 论文阅读笔记
      • Read
      • Read
        • ImageNet Classification with Deep Convolutional Neural Networks
      • Read
        • 论文阅读记录
      • Read
        • Learning Efficient Convolutional Networks through Network Slimming
      • Read
        • M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network
      • Read
        • Rich feature hierarchies for accurate object detection and semantic segmentation
      • Summary
        • 论文阅读总结
      • Notes
        • Batch Regularization
      • Notes
        • batch-regularization
          • Batch Normalization: Accelerating Deep Network Training b y Reducing Internal Covariate Shift
      • Notes
        • batch-regularization
          • Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models
      • Notes
        • batch-regularization
          • DIFFERENTIABLE LEARNING-TO-NORMALIZE VIA SWITCHABLE NORMALIZATION
      • Notes
        • batch-regularization
          • Group Normalization
      • Notes
        • batch-regularization
          • Instance Normalization: The Missing Ingredient for Fast Stylization
      • Notes
        • llm
          • GPT-v1:Improving Language Understanding by Generative Pre-Training
      • Notes
        • llm
          • GPT-v2:Language Models are Unsupervised Multitask Learners
      • Notes
        • llm
          • GPT-v3:Language Models are Few-Shot Learners
      • Notes
        • llm
          • GPT-v4:GPT-4 Technical Report
      • Notes
        • llm
          • 大语言模型(Large Language Models)
      • Notes
        • llm
          • OPT: OPT : Open Pre-trained Transformer Language Models
      • Notes
        • mm-l
          • BLIP: Bootstrapping Language-Image Pre-training
      • Notes
        • mm-l
          • BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Mode
      • Notes
        • mm-l
          • 多模态(MultiModal Machine Learning)
      • Notes
        • Neural Network
      • Notes
        • neural-network
          • ADAM: A METHOD FOR STOCHASTIC OPTIMIZATION
      • Notes
        • neural-network
          • Targeted Dropout
      • Notes
        • neural-network
          • Wide & Deep Learning for Recommender Systems
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自然语言处理(NLP)

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Attention Is All You Need

注意力机制

Attention

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Last updated 2 years ago