Randomly Wired Neural Networks

最新推荐文章于 2023-09-27 16:18:50 发布

SimonChenHere

最新推荐文章于 2023-09-27 16:18:50 发布

阅读量260

点赞数

分类专栏： # GNN实战《GNN & 深度学习& 区块链》文章标签： Random wired NN

本文链接：https://blog.youkuaiyun.com/qq_40199232/article/details/109049997

版权

《GNN & 深度学习& 区块链》同时被 2 个专栏收录

42 篇文章 ¥159.90 ¥299.90

订阅专栏

超级会员免费看

GNN实战

2 篇文章

订阅专栏

本文探讨了Facebook AI Research（FAIR）发布的一篇关于如何利用图论中的随机网络生成算法来构建不同神经网络架构的论文。研究重点在于随机网络生成，对比了传统神经架构搜索中对操作和中间节点连接的优化，提出随机连接可以提供更灵活的网络结构空间。通过ResNet和DenseNet等架构的例子，展示了连接模式对卷积神经网络的影响。论文使用了图论中的ER、BA和WS算法来构造随机无向图，并转换为有向无环图，用于构建神经网络结构。实验结果显示，随机连接神经网络在性能上可与ResNet、ResNeXt等精细设计的网络相媲美，甚至在特定条件下超越它们。

摘要生成于 C知道，由 DeepSeek-R1 满血版支持，前往体验 >

Randomly Wired Neural Networks

A Neural architecture search paper published by FAIR. This paper explore a novel way to look at how we can generate different neural network architectures specifically based on random network generation algorithms from graph theory.

many neural architecture search techniques such as those use reinforcement learning or evolutionary algorithms or even the differentiable architecture search starts algorithm describe the neural architecture search space as a joint optimization of the wiring from nodes representing the state of the neural network and operation meaning what operation is conducted to transform the state of that node .so for example, a different operations could include an average pool