論文筆記：Exploring Neural Networks with Activation Atlases
主要內容 本文在spatial activation visualization的基礎上，通過對每個樣本的activation vector進行數據降維到二維空間中，並且使用歸因向量平均（average the attribution vectors）和特徵反轉（feature visualization）的方法，得到了反映出模型對於整個數據集的特徵關注情況的激活圖譜（activation atl
相關文章
- 1. 論文筆記 - kernel-based non-parametric activation functions for neural networks
- 2. 【Binarized Neural Networks】論文筆記
- 3. 【論文閱讀筆記】PACT：PArameterized Clipping Activation for Quantized Neural Networks
- 4. Neural Activation Constellations: Unsupervised Part Model Discovery with Convolutional Networks
- 5. Understanding Neural Networks Through Deep Visualization 論文筆記
- 6. BinaryConnect: Training Deep Neural Networks with binary weights during propagations 論文筆記
- 7. 論文筆記：ImageNet Classification with Deep Convolutional Neural Networks
- 8. [2018][ICLR]FEW-SHOT LEARNING WITH GRAPH NEURAL NETWORKS 論文筆記
- 9. Bag of Tricks for Image Classification with Convolutional Neural Networks論文筆記
- 10. 06論文筆記《Reducing the Dimensionality of Data with Neural Networks》
- 更多相關文章...
- • ASP.NET Razor - 標記 - ASP.NET 教程
- • CAP理論是什麼？ - NoSQL教程
- • Tomcat學習筆記（史上最全tomcat學習筆記）
- • Scala 中文亂碼解決
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. 字節跳動21屆秋招運營兩輪面試經驗分享
- 2. Java 3 年，25K 多嗎？
- 3. mysql安裝部署
- 4. web前端開發中父鏈和子鏈方式實現通信
- 5. 3.1.6 spark體系之分佈式計算-scala編程-scala中trait特性
- 6. dataframe2
- 7. ThinkFree在線
- 8. 在線畫圖
- 9. devtools熱部署
- 10. 編譯和鏈接
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. 論文筆記 - kernel-based non-parametric activation functions for neural networks
- 2. 【Binarized Neural Networks】論文筆記
- 3. 【論文閱讀筆記】PACT：PArameterized Clipping Activation for Quantized Neural Networks
- 4. Neural Activation Constellations: Unsupervised Part Model Discovery with Convolutional Networks
- 5. Understanding Neural Networks Through Deep Visualization 論文筆記
- 6. BinaryConnect: Training Deep Neural Networks with binary weights during propagations 論文筆記
- 7. 論文筆記：ImageNet Classification with Deep Convolutional Neural Networks
- 8. [2018][ICLR]FEW-SHOT LEARNING WITH GRAPH NEURAL NETWORKS 論文筆記
- 9. Bag of Tricks for Image Classification with Convolutional Neural Networks論文筆記
- 10. 06論文筆記《Reducing the Dimensionality of Data with Neural Networks》