The Expressive Power of Neural Networks: A View from the Width

時間 2021-01-11

標籤 neural networks 简体版

原文原文鏈接

文章目錄概主要內容定理1 定理2 定理3 定理4 定理1的證明 Lu Z, Pu H, Wang F, et al. The expressive power of neural networks: a view from the width[C]. neural information processing systems, 2017: 6232-6240. @article{lu2017

>>阅读原文<<

1. The Unreasonable Effectiveness of Recurrent Neural Networks
2. On the Number of Linear Regions of Deep Neural Networks
3. Exploring the teaching of deep learning in neural networks
4. the english of the simple view
5. Xavier——Understanding the difficulty of training deep feedforward neural networks
6. [paper]Towards Evaluating the Robustness of Neural Networks(C&W)
7. Why LSTMs Stop Your Gradients From Vanishing: A View from the Backwards Pass
8. On the difficulty of training Recurrent Neural Networks
9. The Rise of Meta Learning
10. Applications of Graph Neural Networks
更多相關文章...
• ASP.NET Width 屬性 - ASP.NET 教程
• SQLite 視圖（View） - SQLite教程
• RxJava操作符（一）Creating Observables
• 爲了進字節跳動，我精選了29道Java經典算法題，帶詳細講解

相關標籤/搜索

每日一句

每一个你不满意的现在，都有一个你没有努力的曾经。

最新文章

1. [最佳實踐]瞭解 Eolinker 如何助力遠程辦公
2. katalon studio 安裝教程
3. 精通hibernate（harness hibernate oreilly）中的一個」錯誤「
4. ECharts立體圓柱型
5. 零拷貝總結
6. 6 傳輸層
7. Github協作圖想
8. Cannot load 32-bit SWT libraries on 64-bit JVM
9. IntelliJ IDEA 找其歷史版本
10. Unity3D(二)遊戲對象及組件

本站公眾號

歡迎關注本站公眾號,獲取更多信息

1. The Unreasonable Effectiveness of Recurrent Neural Networks
2. On the Number of Linear Regions of Deep Neural Networks
3. Exploring the teaching of deep learning in neural networks
4. the english of the simple view
5. Xavier——Understanding the difficulty of training deep feedforward neural networks
6. [paper]Towards Evaluating the Robustness of Neural Networks(C&W)
7. Why LSTMs Stop Your Gradients From Vanishing: A View from the Backwards Pass
8. On the difficulty of training Recurrent Neural Networks
9. The Rise of Meta Learning
10. Applications of Graph Neural Networks

>>更多相關文章<<