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- 长短时记忆网络 - Long Short Term Memory Network - LSTM
- 通过遗忘和保留记忆的机制减少梯度爆炸(explode)/ 梯度消失(vanish)。
# Reference
- [ ] [浅谈RNN、LSTM + Kreas实现及应用](https://www.cnblogs.com/shenpings1314/p/10428519.html)
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**S. Hochreiter and J. Schmidhuber, "Long Short-Term Memory," in Neural Computation, vol. 9, no. 8, pp. 1735-1780, 15 Nov. 1997, doi: 10.1162/neco.1997.9.8.1735.**
[https://www.connectedpapers.com/ma…
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## Basic RNNs
Ch. 10: Sequence Modeling: Recurrent and Recursive Nets
Goodfellow et al.
https://www.deeplearningbook.org/
> Accessible blog post
Chris Olah
http://colah.github.io/posts/201…
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# Deep learning is EXPENSIVE
e.g.
train ResNet50 with ImageNet dataset for 80 epochs
80 * 1.3M images * 7.7B ops per img
# Solution?
- **Data Parallelism (large batch training)**
![image](http…
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```
INFO:root:Hong et al. - 2017 - Weakly Supervised Semantic Segmentation using Web-Crawled Videos
References start at 740, end at 821
Total references: 27
Reference type seems to be ReferenceTyp…
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Highlighted in bold is the detail that needs to be implemented. The input has 𝑇 + 20 characters and the signal character is the (𝑇 + 10)th character, then at that moment the network starts outputting…
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## 一言でいうと
強化学習において環境のシミュレーター(World Model)とエージェントの操作(Controller)を分けて考えたモデル。環境は画面の表現をVAEで、時系列の遷移をRNNで学習(次時刻におけるVAEの潜在表現zの分布を予測する)、操作側はVAEの潜在表現とRNNの隠れ層を結合して重みをかけるだけというシンプルさ。
シミュレーターとコントローラーは別個に学習する…
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The image style transfer research over the past year is capable of generating a new image conditioned on a painting’s style. The original [results](https://arxiv.org/abs/1508.06576) were revelatory an…
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there is interesting literature from psy/cognitive science how system 2 might work. it's not describing thorough cognitive architectures, but is relevant nonetheless. I'll grab some and drop them here…
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I am able to generate a reference section by using `\cite{bib_key1}` within a markdown cell and clicking on the book icon displayed for the nbextension "(some) LaTex environments for Jupyter". However…