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### 🚀 Feature
I suggest expanding the system's recurrent components by introducing various recurrent neural networks (RNNs) like vanilla RNN, GRU, and maybe some lesser-know networks like LMU, and ct…
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Implement agents with recurrent networks. Further details TBD.
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Abstract: We present Compositional Attention Networks, a novel fully differentiable neural network architecture, designed to facilitate explicit and expressive reasoning. While many types of neural ne…
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https://arxiv.org/pdf/1803.01271.pdf
#### Subject
+ An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
+ 시퀀스 모델링을 위한 일반 컨볼루션 및 반복 네트워크의 실증적 평가
#### A…
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https://www.microsoft.com/en-us/research/publication/using-recurrent-neural-networks-for-slot-filling-in-spoken-language-understanding/
**Authors**
Grégoire Mesnil
Yann Dauphin
Kaisheng Yao
Yoshua Be…
fin10 updated
8 years ago
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For reference the python version of NEAT allows you to create recurrent and spiking neural networks.
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http://www.aclweb.org/anthology/P16-1125
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I noticed that the current toolkit only supports Conv2D and Dense models. But in practical application and research, we often use time series data to predict. So I want to know whether this theory is …
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I will write my process on bulding a Recurrent Neural Network (RNN) here.
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Some useful links:
- https://blog.floydhub.com/a-beginners-guide-on-recurrent-neural-networks-wi…
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