加载中...

SUPPORT

觉得内容有帮助？请站长喝杯咖啡 ☕

网站所有内容免费，但运维不免费 😭 AI、服务器、域名……你的支持将用来维持网站正常运行，让这个小站还能继续写下去~

微信赞助收款二维码

打开微信扫一扫 · 金额随意

首页知识库教程工具博客资讯术语表面试题库关于?个人中心

← 返回课程

labml.ai Deep Learning Paper Implementations

20 / 38·markdown

adaptive computation

01PonderNet: Learning to Ponder
02Neural Networks with Adaptive Computation

capsule networks

03Capsule Networks

conv mixer

04Patches Are All You Need?

diffusion

05Denoising Diffusion Probabilistic Models (DDPM)

distillation

06Distilling the Knowledge in a Neural Network

gan

07Cycle GAN
08Deep Convolutional Generative Adversarial Networks - DCGAN
09Generative Adversarial Networks - GAN
10StyleGAN 2
11Gradient Penalty for Wasserstein GAN (WGAN-GP)
12Wasserstein GAN - WGAN

graphs

13Graph Attention Networks (GAT)
14Graph Attention Networks v2 (GATv2)

neox

15GPT-NeoX

normalization

16Batch Normalization
17Group Normalization
18Instance Normalization
19Layer Normalization
20Weight Standardization

optimizers

21Optimizers

resnet

22Deep Residual Learning for Image Recognition (ResNet)

rl

23Deep Q Networks (DQN)
24Proximal Policy Optimization - PPO

transformers

25An Attention Free Transformer
26Compressive Transformer
27Fast weights transformer
28Feedback Transformer
29FNet: Mixing Tokens with Fourier Transforms
30Pay Attention to MLPs (gMLP)
31Masked Language Model (MLM)
32MLP-Mixer: An all-MLP Architecture for Vision
33Primer: Searching for Efficient Transformers for Language Modeling
34Switch Transformer
35Vision Transformer (ViT)
36Transformer XL

uncertainty

37Evidential Deep Learning to Quantify Classification Uncertainty
38Neural Networks with Uncertainty Estimation

Chapter 20

Weight Standardization

Weight Standardization

This is a PyTorch implementation of Weight Standardization from the paper Micro-Batch Training with Batch-Channel Normalization and Weight Standardization. We also have an annotated implementation of Batch-Channel Normalization.

上一章

Layer Normalization

下一章

Optimizers

本页镜像自上游仓库，固定版本 33ab0228。许可证：MIT License。原文只读，笔记与划线保存在你的助记词身份下。

阅读进度

0%

整课进度0/38 章 · 0%

快捷键：←/→ 换章 · C 完成 · F 专注 · Esc 退出

阅读设置

字号

行宽

行距

本章笔记

选中正文可划线或写笔记。随助记词身份同步，仅自己可见。

暂无笔记。选中一段文字试试。

本章导航

中文 AI 学习与实践平台。知识库、教程、工具与资讯集中一站，帮你把人工智能真正学到手。

联系support.aimaster.cc@gmail.com

意见反馈 · 内容纠错 · 需求交流

探索

知识库
教程
工具
博客
资讯
术语表
面试题库
关于我们

专题

精选教程
机器学习
深度学习
自然语言处理
计算机视觉

© 2026 AI Master. All rights reserved.

精通人工智能 · ai-master.cc