JavaShuo
欄目
標籤
On the Number of Linear Regions of Deep Neural Networks
時間 2020-12-30
原文
原文鏈接
文獻來源:Montufar G F, Pascanu R, Cho K, et al. On the number of linear regions of deep neural networks[C]//Advances in neural information processing systems. 2014: 2924-2932. https://papers.nips.cc/paper
>>阅读原文<<
相關文章
1.
論文《On the Number of Linear Regions of Deep Neural Networks》翻譯
2.
Exploring the teaching of deep learning in neural networks
3.
Xavier——Understanding the difficulty of training deep feedforward neural networks
4.
The Unreasonable Effectiveness of Recurrent Neural Networks
5.
ICLR2014_Intriguing properties of neural networks
6.
On the difficulty of training Recurrent Neural Networks
7.
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization
8.
CV:翻譯並解讀2019《A Survey of the Recent Architectures of Deep Convolutional Neural Networks》
9.
Fundamentals of Deep Learning – Introduction to Recurrent Neural Networks
10.
Applications of Graph Neural Networks
更多相關文章...
•
XSLT
元素
-
XSLT 教程
•
XSLT
元素
-
XSLT 教程
•
爲了進字節跳動,我精選了29道Java經典算法題,帶詳細講解
•
JDK13 GA發佈:5大特性解讀
相關標籤/搜索
for...of
for..of
dp of dp
networks
regions
neural
linear
number
deep
191.number
Spring教程
0
分享到微博
分享到微信
分享到QQ
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.
gitlab新建分支後,android studio拿不到
2.
Android Wi-Fi 連接/斷開時間
3.
今日頭條面試題+答案,花點時間看看!
4.
小程序時間組件的開發
5.
小程序學習系列一
6.
[微信小程序] 微信小程序學習(一)——起步
7.
硬件
8.
C3盒模型以及他出現的必要性和圓角邊框/前端三
9.
DELL戴爾筆記本關閉觸摸板觸控板WIN10
10.
Java的long和double類型的賦值操作爲什麼不是原子性的?
本站公眾號
歡迎關注本站公眾號,獲取更多信息
相關文章
1.
論文《On the Number of Linear Regions of Deep Neural Networks》翻譯
2.
Exploring the teaching of deep learning in neural networks
3.
Xavier——Understanding the difficulty of training deep feedforward neural networks
4.
The Unreasonable Effectiveness of Recurrent Neural Networks
5.
ICLR2014_Intriguing properties of neural networks
6.
On the difficulty of training Recurrent Neural Networks
7.
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization
8.
CV:翻譯並解讀2019《A Survey of the Recent Architectures of Deep Convolutional Neural Networks》
9.
Fundamentals of Deep Learning – Introduction to Recurrent Neural Networks
10.
Applications of Graph Neural Networks
>>更多相關文章<<